JP7653768B2 - Vehicle type discrimination device, vehicle type discrimination method, and program - Google Patents

Description

This disclosure relates to a vehicle type discrimination device, a vehicle type discrimination method, and a program.

On toll roads, different tolls may be charged depending on the type of vehicle traveling on the road. Toll booths on such toll roads are equipped with vehicle type discrimination devices to discriminate the type of vehicle. The vehicle type discrimination device discriminates the type of vehicle based on the external characteristics of the vehicle (width, length, height, number of axles, etc.), license plate information, etc. For example, Patent Document 1 describes a vehicle type discrimination device that measures the number of axles and width of a vehicle from an image taken of the side of the vehicle to discriminate the vehicle type.

JP 2019-197314 A

In addition, different vehicle type tolls may apply depending on whether or not the vehicle is being towed. For example, if a vehicle (tow vehicle) is towing a single-axle towed vehicle, a higher toll (one rank higher) than the vehicle's original vehicle type will be applied. In this case, the vehicle type discrimination device needs to correctly discriminate that the vehicle type is one rank higher than the tow vehicle's vehicle type. However, it may be difficult to uniquely determine whether or not the vehicle is being towed from the number of axles. For this reason, there is a possibility that the accuracy of vehicle type discrimination may decrease depending on whether or not the vehicle is being towed.

This disclosure was made in consideration of these problems, and provides a vehicle type discrimination device, a vehicle type discrimination method, and a program that can accurately discriminate the vehicle type regardless of whether or not the vehicle is being towed.

According to one aspect of the present disclosure, a vehicle type discrimination device includes a tire pattern generation unit that generates a tire pattern indicating the number of tires provided at one end of each axle of the vehicle based on sensor information capable of detecting the characteristics of the vehicle's tires, a candidate identification unit that compares the generated tire pattern with pre-stored reference data that associates tire patterns and vehicle types to identify a first vehicle type candidate for the vehicle, and a vehicle type determination unit that determines the vehicle type based on the first vehicle type candidate.

According to one aspect of the present disclosure, a vehicle type determination method includes the steps of: generating a tire pattern indicating the number of tires provided at one end of each axle of a vehicle based on sensor information capable of detecting the characteristics of the vehicle's tires; comparing the generated tire pattern with pre-stored reference data that associates tire patterns with vehicle types to identify a first vehicle type candidate for the vehicle; and determining the vehicle type based on the first vehicle type candidate.

According to one aspect of the present disclosure, the program causes a computer of a vehicle type discrimination device to execute the steps of: generating a tire pattern indicating the number of tires provided at one end of each axle of the vehicle based on sensor information capable of detecting the characteristics of the vehicle's tires; comparing the generated tire pattern with pre-stored reference data associating tire patterns and vehicle types to identify a first vehicle type candidate for the vehicle; and determining the vehicle type based on the first vehicle type candidate.

The vehicle type discrimination device, vehicle type discrimination method, and program disclosed herein can accurately discriminate the vehicle type regardless of whether or not the vehicle is being towed.

1 is a diagram illustrating an overview of a vehicle type discrimination system according to an embodiment of the present disclosure. FIG. 2 is a diagram illustrating a functional configuration of a vehicle type discrimination device according to an embodiment of the present disclosure. 4 is a flowchart illustrating an example of a process of the vehicle type discrimination device according to an embodiment of the present disclosure. FIG. 13 is a diagram illustrating an example of reference data according to an embodiment of the present disclosure. FIG. 13 is a diagram illustrating an example of additional data according to an embodiment of the present disclosure. FIG. 2 is a diagram illustrating an example of a hardware configuration of the vehicle type discrimination device according to an embodiment of the present disclosure.

The vehicle type discrimination system 1 according to the first embodiment of the present disclosure will be described below with reference to Figures 1 to 6.

(Overall composition)
FIG. 1 is a diagram illustrating an overview of a vehicle type discrimination system according to an embodiment of the present disclosure.
The vehicle type discrimination system 1 according to this embodiment is installed, for example, at an entrance toll booth or an exit toll booth of a toll road, and discriminates the vehicle type of a passing vehicle. In this embodiment, an example will be described in which the vehicle type discrimination system 1 is installed at an exit toll booth. As shown in FIG. 1, the exit toll booth has a lane L leading from the toll road to a general road. Each device constituting the vehicle type discrimination system 1 is installed on the lane L or on islands I laid on both sides of the lane L, and discriminates the vehicle type of a vehicle A traveling on the lane L.

In the following explanation, the direction in which lane L extends (±X direction in Fig. 1) is referred to as the "lane direction", the toll road side of lane L (-X side in Fig. 1) is referred to as the "upstream side", and the general road side (+X side in Fig. 1) is referred to as the "downstream side". In addition, the width direction of lane L (±Y direction in Fig. 1) is referred to as the "lane width direction", and the up-down direction of vehicle A (±Z direction in Fig. 1) is referred to as the "height direction".

As shown in FIG. 1, the vehicle type discrimination system 1 includes a vehicle type discrimination device 10, a vehicle detector 11, a tire detection sensor 12, and a license plate reader 13.

The vehicle type discrimination device 10 is installed on the island I. The vehicle type discrimination device 10 acquires sensor information about a vehicle A traveling in lane L from various sensors (vehicle detector 11, footboard 12, license plate reader 13) of the vehicle type discrimination system 1, and discriminates the vehicle type of the vehicle A.

The vehicle detector 11 is installed on the most upstream side (-X side) in the lane direction and detects the entry and passage of vehicle A traveling on lane L. For example, as shown in FIG. 1, the vehicle detector 11 is a transmissive optical sensor that extends in the height direction (±Z direction) on island I and has a corresponding light projecting tower and a light receiving tower on either side of lane L. The vehicle detector 11 outputs a vehicle detection signal (sensor information) that can detect the entry and passage (presence and absence) of vehicle A to the vehicle type discrimination device 10 based on whether the detection light projected from the light projecting tower is received by the light receiving tower. In other embodiments, the vehicle detector 11 may be a reflective optical sensor.

The tire detection sensor 12 is a sensor for detecting the tires of the vehicle A traveling on the lane L. In this embodiment, an example will be described in which the tire detection sensor 12 is a tread. The tire detection sensor 12 is embedded in the road surface of the lane L so as to extend in the lane width direction (±Y direction) at the same position as the vehicle detector 11 in the lane direction (±X direction). The tire detection sensor 12 outputs a step detection signal (sensor information) corresponding to the stepping on by the tires of the vehicle A to the vehicle type discrimination device 10 through an internal electrical conductivity sensor.

The license plate reader 13 (hereinafter also referred to as the "NP reader") is installed on island I downstream (+X side) in the lane direction from the vehicle detector 11. The NP reader 13 captures an image including the license plate of vehicle A when the vehicle detector 11 detects that vehicle A has entered lane L. The NP reader 13 obtains license plate information (sensor information) of vehicle A by performing a specified image processing on the captured image. The license plate information includes the size, color, license plate number, etc. of the license plate.

The vehicle type identified by the vehicle type identification device 10 is transmitted to the toll machine 20. In the example of FIG. 1, the toll machine 20 is installed in manned booth B located downstream (+X side) in the lane direction from the vehicle type identification system 1, and is a device for assisting the toll collector in collecting the toll. The toll machine 20 calculates the toll for vehicle A based on the vehicle type received from the vehicle type identification device 10.

(Functional configuration of vehicle type discrimination device)
FIG. 2 is a diagram illustrating a functional configuration of the vehicle type discrimination device according to an embodiment of the present disclosure.
As shown in FIG. 2, the vehicle type discrimination device 10 includes a CPU 100 and a storage medium 110 .

The CPU 100 is a processor that controls the overall operation of the vehicle type discrimination device 10, and functions as a tire pattern generation unit 101, a candidate identification unit 102, a vehicle type determination unit 103, and a reference data update unit 104 by operating according to a predetermined program.

The tire pattern generation unit 101 generates a tire pattern indicating the number of tires provided at one end of each axle of vehicle A based on sensor information (foot-on detection signal) capable of detecting the characteristics of the tires of vehicle A.

The candidate identification unit 102 compares the generated tire pattern with reference data that associates tire patterns and vehicle models and that is pre-stored in the storage medium 110, and identifies a candidate vehicle model for vehicle A (hereinafter also referred to as the "first vehicle model candidate").

The vehicle type determination unit 103 determines the vehicle type of vehicle A based on the first vehicle type candidate.

The reference data update unit 104 obtains the model of vehicle A specified through the toll machine 20, and adds additional data associating the generated tire pattern with the specified model to the reference data.

The storage medium 110 is a so-called auxiliary storage device, such as a hard disk drive (HDD) or a solid state drive (SSD). Reference data is stored in advance in the storage medium 110. In addition, the storage medium 110 sequentially stores various data acquired or generated by the vehicle type discrimination device.

(Processing flow of the vehicle type discrimination device)
FIG. 3 is a flowchart illustrating an example of a process of the vehicle type discrimination device according to an embodiment of the present disclosure.
Hereinafter, the flow of processing by the vehicle type discrimination device 10 to discriminate the vehicle type of the vehicle A will be described with reference to FIG.

As shown in FIG. 3, the tire pattern generation unit 101 of the vehicle type discrimination device 10 receives a vehicle detection signal from the vehicle detector 11 indicating that vehicle A has entered lane L (step S01). The tire pattern generation unit 101 then generates a tire pattern for vehicle A based on the stepping detection signal received from the tire detection sensor 12 while the vehicle detector 11 is detecting the presence of vehicle A (step S02).

The trample detection signal includes a signal indicating the presence or absence of trampling by the tire of vehicle A (a signal indicating the axle), a signal indicating the trample position in the lane width direction (±Y direction in FIG. 1) on the tire detection sensor 12, and a signal indicating the tire width. The tire pattern generation unit 101 counts the signals indicating the axles to identify the axle positions of vehicle A (first axle, second axle, ...). The tire pattern generation unit 101 also identifies the number of tires (connected number) provided at one end of each axle of vehicle A based on the signal indicating the tire width. For example, the tire pattern generation unit 101 according to this embodiment identifies a single tire (connected number = 1) when the tire width is less than a reference value, and a double tire (connected number = 2) when the tire width is equal to or greater than the reference value. In another embodiment, the tire pattern generation unit 101 may further identify that three tires are connected in series. For example, the tire pattern generation unit 101 identifies the connected number of tires as "3" when the tire width is equal to or greater than a second reference value (maximum width of double tires).

Then, the tire pattern generation unit 101 generates a tire pattern indicating whether the tires on each axle of vehicle A are single tires or double tires. The tire pattern is represented by a string of letters, for example, in which "S" indicating a single tire and "D" indicating a double tire are arranged in order starting from the first axle. Specifically, the tire pattern of a vehicle with a single tire on the first axle and a double tire on the second axle is "SD." Similarly, if a two-axle vehicle with single tires on the first and second axles is towing a towed vehicle with a single axle that is equipped with a double tire, the tire pattern of this vehicle is "SSD."

Next, the candidate identification unit 102 compares the generated tire pattern with reference data D1 (Figure 4) that associates tire patterns and vehicle models and that is pre-stored in the storage medium 110, and determines whether there is reference data that matches the generated tire pattern (step S03).

FIG. 4 is a diagram illustrating an example of reference data according to an embodiment of the present disclosure.
As shown in FIG. 4, reference data D1 is data that lists which tire patterns can be used for each of a number of vehicle types (e.g., vehicle types 1 to 5). Where "applicable" is written in reference data D1, this indicates that the combination of tire pattern and vehicle type exists. Where "-" is written in reference data D1, this indicates that the combination of tire pattern and vehicle type does not exist (is not applicable). Furthermore, reference data D1 includes both combinations of tire pattern and vehicle type of towing vehicles (vehicle and towed vehicle) and combinations of tire pattern and vehicle type of vehicles that are not towing.

The reference data D1 may include data indicating an abnormal tire pattern. For example, it is assumed that there are no vehicles with tire patterns of "SDSD" or "DSSS". In this case, for these tire patterns, instead of information indicating whether the vehicle type is matched or not, "abnormal" may be input, indicating that an abnormality (false detection, failure, etc.) has occurred in the vehicle type discrimination system 1. Note that the data indicating an abnormal tire pattern may further include an estimated cause of the abnormality (failure of the vehicle detector 11 to separate the leading vehicle from the following vehicle, false detection of single tire/double tire by the tire detection sensor 12, etc.).

This reference data D1 may be created by a collector or other person inputting the tire pattern and vehicle type, or it may be created based on statistical data of combinations of tire patterns and vehicle types detected in the past.

If data matching the generated tire pattern is present in the reference data D1 (step S03: YES), the candidate identification unit 102 refers to this data and further determines whether there is a vehicle model candidate that matches the generated tire pattern (step S04).

For example, suppose the generated tire pattern is "SS" (single tires on the first and second axles). Reference data D1 contains data that matches the generated tire pattern "SS" (step S03: YES). Furthermore, there are four vehicle models that fit this tire pattern "SS" (vehicle models with "applicable" written on them): "Vehicle Model 2," "Vehicle Model 3," "Vehicle Model 4," and "Vehicle Model 5" (step S04: YES). In this case, the candidate identification unit 102 identifies these four vehicle models as the first vehicle model candidates for vehicle A (step S05).

Next, the vehicle model determination unit 103 determines whether the candidate identification unit 102 has identified only one first vehicle model candidate (step S06). If there is only one first vehicle model candidate (step S06: YES), the vehicle model determination unit 103 identifies the first vehicle model candidate as the vehicle model of vehicle A (step S07). In the example of FIG. 4, if the tire pattern of vehicle A is "SDDDD" (single tire on the first axle, double tires on the second to fifth axles), the candidate identification unit 102 identifies the first vehicle model candidate of vehicle A as "vehicle model 1" in step S03. Then, since there is only one first vehicle model candidate, "vehicle model 1" (step S06: YES), the vehicle model determination unit 103 identifies the vehicle model of vehicle A as the first vehicle model candidate, "vehicle model 1" (step S07).

On the other hand, if the first vehicle model candidate includes multiple vehicle models (step S06: NO), the vehicle model determination unit 103 performs a process to further narrow down the vehicle model candidates for vehicle A (step S09).

For example, the range of values that a vehicle's tread width can take varies depending on the vehicle type. Therefore, the vehicle type determination unit 103 measures the tread width of vehicle A based on the stepping signal received from the tire detection sensor 12, and identifies the vehicle type that matches the measured tread width as the second vehicle type candidate. For example, if the measured tread width is included in the tread width range of "Vehicle type 4" and "Vehicle type 5" but not included in the tread width range of "Vehicle type 1" to "Vehicle type 3", the vehicle type determination unit 103 identifies "Vehicle type 4" and "Vehicle type 5" as the second vehicle type candidates. Then, the vehicle type determination unit 103 narrows down the vehicle type candidates by excluding the vehicle types that are included in the first vehicle type candidates but are not included in the second vehicle type candidates. Note that the vehicle type determination unit 103 may use a sensor other than the tire detection sensor 12, such as determining the tread width of vehicle A based on a signal obtained by measuring with a rangefinder (not shown) from the left and right of the lane.

It is also possible to narrow down the vehicle model candidates using license plate information. The vehicle model determination unit 103 identifies a vehicle model that matches the license plate information received from the NP reader 13 as a third vehicle model candidate. The vehicle model determination unit 103 then narrows down the vehicle model candidates by excluding, from among the first vehicle model candidates, vehicle models that are not included in the third vehicle model candidates.

The vehicle model determination unit 103 may narrow down the vehicle model candidates based on either the tread width or the license plate information, or, if it is not possible to identify a single vehicle model candidate based on either one, it may narrow down the vehicle model candidates based on both. When the vehicle model determination unit 103 narrows down the vehicle model candidates for vehicle A to only one in this manner, it identifies this vehicle model candidate as the vehicle model of vehicle A (step S07).

Next, when the vehicle type determination unit 103 identifies the vehicle type of vehicle A, it transmits the identified vehicle type as the vehicle type determination result to the toll machine 20 (step S08). The toll machine 20 calculates the toll for vehicle A based on the vehicle type received from the vehicle type determination device 10.

For example, suppose the tire pattern generated is "SDSD." In the example of FIG. 4, such a tire pattern exists in the reference data D1 (step S03: YES), but there is no applicable vehicle model (step S04: NO), indicating an abnormality. In this case, the candidate specification unit 102 notifies the toll machine 20 that an abnormality has occurred in the detection of the tire pattern (step S10), and requests the toll machine 20 to specify the vehicle model of vehicle A (step S11). This allows the vehicle type discrimination device 10 to notify the toll collector of the abnormality in the vehicle type discrimination system 1, and to prompt the toll machine 20 to perform processing such as toll calculation based on the vehicle model of vehicle A specified by the toll collector.

Furthermore, if the generated tire pattern does not exist in the reference data D1 (step S03: NO), the candidate identification unit 102 requests the toll machine 20 to specify the vehicle type of vehicle A (step S12). The toll collector stationed at manned booth B then visually checks vehicle A to identify the vehicle type, and performs an operation to identify the vehicle type of vehicle A through the toll machine 20. The toll machine 20 calculates the toll based on the vehicle type specified by the toll collector.

The vehicle type specified by the toll collector is transmitted to the vehicle type identification device 10 via the toll machine 20. When the reference data update unit 104 of the vehicle type identification device 10 receives the specified vehicle type from the toll machine 20, it associates it with the tire pattern generated in step S02 and stores it in the storage medium 110 as additional data D2 (Figure 5) (step S13).

FIG. 5 is a diagram illustrating an example of additional data according to an embodiment of the present disclosure.
For example, let us say that the tire pattern "SSDD" (the first and second axles are single tires, and the third and fourth axles are double tires) did not exist in the reference data D1. As shown in the example of FIG. 5, the tire pattern "SSDD" may have multiple cases, such as a case where it is a towing vehicle (two axles) towing a towed vehicle (two axles) and corresponds to vehicle type 3, or a case where it is a single vehicle (four axles) and corresponds to vehicle type 2. For this reason, when a new tire pattern "SSDD" that does not exist in the reference data D1 is generated (step S03: NO), the reference data update unit 104 stores and accumulates in the storage medium 110 additional data D2 that associates this new tire pattern "SSDD" with the vehicle type ("vehicle type 3" or "vehicle type 2") specified by the toll collector through the toll machine 20. Furthermore, when a predetermined amount or more of additional data D2 related to the new tire pattern "SSDD" is accumulated, the reference data update unit 104 adds data combining the tire pattern "SSDD" and the applicability/non-applicability of each vehicle model to the reference data D1. In this way, the reference data update unit 104 can further enrich the contents of the reference data D1.

(Hardware configuration of vehicle type discrimination device)
FIG. 6 is a diagram illustrating an example of a hardware configuration of the vehicle type discrimination device according to an embodiment of the present disclosure.
Hereinafter, the hardware configuration of the vehicle type discrimination device 10 according to this embodiment will be described with reference to FIG.

The computer 900 includes a processor 901, a main memory device 902, an auxiliary memory device 903, and an interface 904.

The vehicle type discrimination device 10 described above is implemented in one or more computers 900. The operation of each of the above-mentioned functional units is stored in the auxiliary storage device 903 in the form of a program. The processor 901 reads the program from the auxiliary storage device 903, expands it in the main storage device 902, and executes the above-mentioned processing in accordance with the program. The processor 901 also secures storage areas in the main storage device 902 corresponding to each of the above-mentioned storage units in accordance with the program. Examples of the processor 901 include a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), and a microprocessor.

The program may be for implementing part of the functions to be performed by the computer 900. For example, the program may be implemented by combining it with other programs already stored in the auxiliary storage device 903 or other programs implemented in other devices. In another embodiment, the computer 900 may include a custom LSI (Large Scale Integrated Circuit) such as a PLD (Programmable Logic Device) in addition to or instead of the above configuration. Examples of PLDs include PAL (Programmable Array Logic), GAL (Generic Array Logic), CPLD (Complex Programmable Logic Device), and FPGA (Field Programmable Gate Array). In this case, part or all of the functions implemented by the processor 901 may be implemented by the integrated circuit. Such an integrated circuit is also included as an example of a processor.

Examples of the auxiliary storage device 903 include a hard disk drive (HDD), a solid state drive (SSD), a magnetic disk, a magneto-optical disk, a compact disc read only memory (CD-ROM), a digital versatile disc read only memory (DVD-ROM), and a semiconductor memory. The auxiliary storage device 903 may be an internal medium directly connected to the bus of the computer 900, or an external storage device 910 connected to the computer 900 via an interface 904 or a communication line. In addition, when the program is distributed to the computer 900 via a communication line, the computer 900 that receives the program may expand the program in the main storage device 902 and execute the above-mentioned processing. In at least one embodiment, the auxiliary storage device 903 is a non-transitory tangible storage medium.

Furthermore, the program may be for realizing a part of the above-mentioned functions.
Furthermore, the program may be a so-called differential file (differential program) that realizes the above-mentioned functions in combination with another program already stored in the auxiliary storage device 903.

(Action, Effect)
As described above, the vehicle type discrimination device 10 according to this embodiment compares the reference data D1 with the tire pattern generated based on the stepping-on detection signal to identify a first vehicle type candidate for vehicle A, and identifies the vehicle type of vehicle A based on the identified first vehicle type candidate. In this manner, the vehicle type discrimination device 10 can identify a vehicle type candidate that applies to vehicle A from the tire pattern of vehicle A and the reference data D1, regardless of whether or not the vehicle is towed. This allows the vehicle type discrimination device 10 to accurately discriminate the vehicle type of vehicle A without performing complicated processing to detect whether or not the vehicle is towed.

The vehicle type discrimination device 10 also determines the vehicle type by excluding from the first vehicle type candidates those vehicle types that are not included in the second vehicle type candidates identified from the tread width of vehicle A. As a result, even if the vehicle type discrimination device 10 is unable to narrow down to one vehicle type from the tire pattern, it can further narrow down the vehicle type candidates from the tread width and identify the vehicle type of vehicle A.

The vehicle type discrimination device 10 also determines the vehicle type by excluding from the first vehicle type candidates those vehicle types that are not included in the third vehicle type candidates identified from the license plate information of vehicle A. As a result, even if the vehicle type discrimination device 10 is unable to narrow down to one vehicle type from the tire pattern, it can further narrow down the vehicle type candidates from the license plate information and identify the vehicle type of vehicle A.

In addition, if the reference data D1 that matches the generated tire pattern indicates an abnormality, the vehicle type identification device 10 notifies the toll machine 20 that an abnormality has occurred in the detection of the tire pattern. This allows the vehicle type identification device 10 to promptly make the toll collector aware of any abnormalities in the various sensor devices of the vehicle type identification system 1.

In addition, if there is no reference data D1 that matches the generated tire pattern, the vehicle type discrimination device 10 requests the toll machine 20 to specify the vehicle type of vehicle A. As a result, if a new tire pattern that does not exist in the reference data D1 is detected, the vehicle type discrimination device 10 can prompt the toll collector through the toll machine 20 to specify an appropriate vehicle type.

The vehicle type discrimination device 10 also includes a reference data update unit 104 that acquires the vehicle type of vehicle A specified through the toll machine 20 and adds additional data D2, which associates the generated tire pattern with the specified vehicle type, to the reference data D1. As a result, even if the vehicle type discrimination device 10 detects a tire pattern that does not exist in the reference data D1, it can add a new tire pattern to the reference data based on the vehicle type specified by the toll collector and use it in subsequent vehicle type discrimination processes.

Although the embodiments of the present disclosure have been described in detail above, the present invention is not limited to these embodiments and some design changes are possible without departing from the technical concept of the present invention.

For example, in the above embodiment, the tire detection sensor 12 is a tread, but the present invention is not limited to this. In other embodiments, the tire detection sensor 12 may be a non-contact sensor such as a camera or a laser scanner. In this case, the tire detection sensor 12 outputs an image of the tires of the vehicle A or the results of scanning the tires of the vehicle A with laser light as sensor information to the vehicle type discrimination device 10.

In addition, when the tire detection sensor 12 is a camera, the tire pattern generation unit 101 of the vehicle type discrimination device 10 detects the number of axles of the vehicle A and the number of tires (single tire/double tire) attached to one end of each axle by applying a predetermined image processing to the image received from the tire detection sensor 12. In addition, when the tire detection sensor 12 is a laser scanner, the tire pattern generation unit 101 detects the number of axles of the vehicle A and the number of tires (single tire/double tire) attached to one end of each axle based on the shape of the tires and/or wheels obtained from the scan results.

<Additional Notes>
The vehicle type discrimination device, the vehicle type discrimination method, and the program described in the above-described embodiments can be understood, for example, as follows.

According to a first aspect of the present disclosure, a vehicle type discrimination device (10) includes a tire pattern generation unit (101) that generates a tire pattern indicating the number of tires provided at one end of each axle of the vehicle based on sensor information capable of detecting the characteristics of the vehicle's tires, a candidate identification unit (102) that compares the generated tire pattern with pre-stored reference data (D1) that associates tire patterns and vehicle types, and identifies a first vehicle type candidate for the vehicle, and a vehicle type determination unit (103) that determines the vehicle type based on the first vehicle type candidate.

In this way, the vehicle type discrimination device can identify vehicle type candidates that apply to the vehicle from the vehicle's tire pattern and reference data, regardless of whether the vehicle is being towed. This allows the vehicle type discrimination device to accurately discriminate the vehicle type without having to perform complex processing to detect whether the vehicle is being towed.

According to a second aspect of the present disclosure, in the vehicle type discrimination device (10) according to the first aspect, the vehicle type determination unit (103) measures the tread width of the vehicle, and determines the vehicle type by excluding, from the first vehicle type candidates, vehicle types that are not included in the second vehicle type candidates identified from the tread width.

As a result, even if the vehicle type discrimination device is unable to narrow down to one vehicle type from the tire pattern, it can further narrow down the vehicle type candidates from the tread width and identify the vehicle type. Note that since the tread width can be measured from each axle of the vehicle, the timing at which it can be obtained depends on the number of axles. This makes it possible to obtain many timings at which the vehicle type can be identified.

According to a third aspect of the present disclosure, in the vehicle type discrimination device (10) according to the first or second aspect, the vehicle type determination unit (103) acquires license plate information of the vehicle from a license plate reader (13), and determines the vehicle type of the vehicle by excluding, from the first vehicle type candidates, vehicle types that are not included in the third vehicle type candidates identified from the license plate information.

As a result, even if the vehicle type discrimination device is unable to narrow down to one vehicle type based on the tire pattern, it can further narrow down the vehicle type candidates from the license plate information and identify the vehicle type. Note that license plate information can be obtained from information on a narrower area than the vehicle's exterior (entire vehicle body) on which the license plate is attached. Therefore, since it is sufficient to obtain limited information around the license plate, there is a lower chance of failure to obtain information compared to obtaining information on the vehicle's exterior, which is a wider area. As a result, there is a higher chance of obtaining information to further narrow down the vehicle type candidates, and the possibility of identifying the vehicle type can be increased.

According to a fourth aspect of the present disclosure, in the vehicle type discrimination device (10) according to any one of the first to third aspects, the candidate identification unit (102) notifies that an abnormality has occurred in the detection of the tire pattern if the reference data that matches the generated tire pattern indicates an abnormality.

This allows the vehicle type discrimination device to quickly alert the collector to any abnormalities in the various sensor devices.

According to a fifth aspect of the present disclosure, in the vehicle type discrimination device (10) according to any one of the first to fourth aspects, the candidate specification unit (102) requests specification of the vehicle type when there is no reference data that matches the generated tire pattern.

As a result, if the vehicle type discrimination device detects a new tire pattern that does not exist in the reference data, it can prompt the collector to specify the appropriate vehicle type.

According to a sixth aspect of the present disclosure, the vehicle type discrimination device (10) according to the fifth aspect further includes a reference data update unit (104) that acquires the specified vehicle type and adds additional data that associates the generated tire pattern with the specified vehicle type to the reference data.

As a result, even if the vehicle type discrimination device detects a tire pattern that does not exist in the reference data, it can add a new tire pattern to the reference data based on the vehicle type specified by the collector and use it in subsequent vehicle type discrimination processes.

According to a seventh aspect of the present disclosure, a vehicle type determination method includes the steps of: generating a tire pattern indicating whether the tires on each axle of the vehicle are single tires or double tires based on sensor information capable of detecting the characteristics of the vehicle's tires; comparing the generated tire pattern with pre-stored reference data that associates tire patterns with vehicle types to identify a first vehicle type candidate for the vehicle; and determining the vehicle type based on the first vehicle type candidate.

According to an eighth aspect of the present disclosure, the program causes a computer (900) of a vehicle type discrimination device (10) to execute the steps of: generating a tire pattern indicating whether the tires for each axle of the vehicle are single tires or double tires based on sensor information capable of detecting the characteristics of the vehicle's tires; comparing the generated tire pattern with pre-stored reference data that associates tire patterns and vehicle types; and identifying a first vehicle type candidate for the vehicle based on the first vehicle type candidate.

1 Vehicle type discrimination system 10 Vehicle type discrimination device 100 CPU
101 Tire pattern generation unit 102 Candidate specification unit 103 Vehicle type determination unit 104 Reference data update unit 110 Storage medium 11 Vehicle detector 12 Tire detection sensor 13 Number plate reader (NP reader)
20 Fee machine 900 Computer

Claims (8)

A tire pattern generating unit that identifies the number of tires provided at one end of each axle of the vehicle based on sensor information capable of detecting the characteristics of the tires of the vehicle, and generates a tire pattern in which each of the identified multiple tire numbers is arranged in order from the leading axle;
a candidate identification unit that identifies a first candidate vehicle type of the vehicle by comparing the generated tire pattern with pre-stored reference data that associates tire patterns with vehicle types;
a vehicle type determination unit that determines a vehicle type of the vehicle based on the first vehicle type candidate;
Equipped with
The candidate identification unit identifies the first vehicle type candidates of the vehicles including the towing vehicle and the single vehicle based on the reference data including data associating tire patterns and vehicle types of towing vehicles including a towed vehicle and a vehicle towing the towed vehicle, and data associating tire patterns and vehicle types of a single vehicle that is not towing.
Vehicle type identification device. The vehicle type determination unit
measuring the tread width of the vehicle;
determining a vehicle model of the vehicle by excluding, from the first vehicle model candidates, vehicle models that are not included in the second vehicle model candidates identified based on the tread width;
The vehicle type discrimination device according to claim 1. The vehicle type determination unit
acquiring license plate information of the vehicle from a license plate reader;
determining a vehicle model of the vehicle by excluding, from the first vehicle model candidates, vehicle models that are not included in a third vehicle model candidate identified from the license plate information;
3. The vehicle type discrimination device according to claim 1 or 2. the candidate identification unit notifies the user that an abnormality has occurred in detection of the tire pattern when the reference data that matches the generated tire pattern indicates an abnormality.
The vehicle type discrimination device according to any one of claims 1 to 3. the candidate identification unit, when there is no reference data that matches the generated tire pattern, requests designation of a vehicle model of the vehicle.
The vehicle type discrimination device according to any one of claims 1 to 4. a reference data update unit that acquires a specified vehicle model of the vehicle and adds additional data that associates the generated tire pattern with the specified vehicle model to the reference data;
The vehicle type discrimination device according to claim 5. A step of identifying the number of tires provided at one end of each axle of the vehicle based on sensor information capable of detecting the characteristics of the tires of the vehicle, and generating a tire pattern in which each of the identified multiple tire numbers is arranged in order from the leading axle;
comparing the tire pattern generated with pre-stored reference data associating tire patterns with vehicle models to identify a first vehicle model candidate of the vehicle;
determining a vehicle type of the vehicle based on the first vehicle type candidate;
having
The step of identifying the first vehicle type candidates identifies the first vehicle type candidates of the vehicles including the towing vehicle and the single vehicle based on the reference data including data correlating tire patterns and vehicle types of towing vehicles including a towed vehicle and a vehicle towing the towed vehicle, and data correlating tire patterns and vehicle types of a single vehicle that is not towing.
How to identify the vehicle type. A step of identifying the number of tires provided at one end of each axle of the vehicle based on sensor information capable of detecting the characteristics of the tires of the vehicle, and generating a tire pattern in which each of the identified multiple tire numbers is arranged in order from the leading axle;
comparing the tire pattern generated with pre-stored reference data associating tire patterns with vehicle models to identify a first vehicle model candidate of the vehicle;
determining a vehicle type of the vehicle based on the first vehicle type candidate;
A program for causing a computer of a vehicle type discrimination device to execute the above,
The step of identifying the first vehicle type candidates identifies the first vehicle type candidates of the vehicles including the towing vehicle and the single vehicle based on the reference data including data correlating tire patterns and vehicle types of towing vehicles including a towed vehicle and a vehicle towing the towed vehicle, and data correlating tire patterns and vehicle types of a single vehicle that is not towing.
program .

Images