JP2021108013A - Congestion prediction method and congestion prediction device - Google Patents

Abstract

To provide a congestion prediction method and congestion prediction device capable of correctly predicting a congestion and contributing to convenience of a person who uses congestion prediction data using inter-vehicle distance information.SOLUTION: A congestion prediction device includes: imaging devices 21, 23 arranged in an own vehicle so as to image a front vehicle and a following rear vehicle which are traveling on a travel lane adjacent to an own vehicle travel lane; a processing device 32 for obtaining a distance between front and rear vehicles based on data from the imaging devices; and a server 28 for collecting an inter-vehicle distance output from the processing device and measurement position information and predicting a congestion based on the inter-vehicle distance information for each measurement position. When a congestion is predicted, a front side and a rear side are imaged by the imaging means mounted on an own vehicle, so as to use an inter-vehicle distance between a front vehicle and a following rear vehicle which are traveling on a travel lane adjacent to an own vehicle travel lane.SELECTED DRAWING: Figure 2

Description

The present invention is a traffic jam prediction method and a traffic jam prediction method that enables a user to easily use the prediction data by collecting the traffic jam information and predicting the traffic jam from the collected data. Regarding the device.

On expressways and the like, a method of detecting the passing speed of a vehicle as the passing amount and predicting traffic congestion based on this information has been presented (Patent Document 1). However, this method is not real-time, it is a fixed point and the equipment is large-scale.

Therefore, a method of predicting traffic congestion based on the information acquired by the own vehicle has also been proposed (Patent Document 2). According to this known method, while detecting the speed of the own vehicle, an image on the overtaking lane in front of the own vehicle is captured, and when the passage of two vehicles on the overtaking lane is detected, both of them are detected. The time difference, the distance between vehicles, and the speed are calculated, the traffic volume in the overtaking lane is calculated, and the traffic congestion is predicted from this traffic volume.

However, the above-mentioned conventional method has a problem that real-time measurement cannot be performed because a heavy calculation load such as calculation of traffic volume and congestion cannot be predicted until two vehicles in front pass by. Further, when two vehicles in front pass through, there are drawbacks such as the case where the preceding vehicle is behind the vehicle behind at the time of shooting, and the measurement cannot be performed or the error becomes large even if the measurement is performed.

Japanese Unexamined Patent Publication No. 2006-309735 JP-A-2019-16081

The present invention focuses on the above-mentioned conventional problems, quickly grasps the inter-vehicle distance between two vehicles in the front and rear on the adjacent lane including the overtaking lane with little error during measurement, and collects the inter-vehicle distance information. Since the traffic jam is predicted, it is possible to more accurately predict the traffic jam, and to provide a traffic jam prediction method and a traffic jam prediction device that can be used for the convenience of those who use the traffic jam prediction data using the inter-vehicle distance information. The purpose.

According to the present invention, anyone who has a carry-on device such as a smartphone can easily obtain a material for determining whether or not a traffic jam occurs at a low cost, and collects this data so that the traffic jam can be predicted. It is to make it possible to provide it for the convenience of the user.

In order to achieve the above object, the traffic jam prediction method according to the present invention photographs the front and the rear by a photographing means mounted on the own vehicle at the time of the traffic jam prediction, and the front while traveling in the traveling lane adjacent to the own vehicle traveling lane. The inter-vehicle distance between the vehicle and the vehicle behind it is used.

Further, the present invention calculates the inter-vehicle distance between the front vehicle traveling in the traveling lane adjacent to the own vehicle traveling lane and the following rear vehicle from the captured images before and after the vehicle, and outputs this inter-vehicle distance. , The output inter-vehicle distance is collected, and traffic congestion is predicted based on the collected inter-vehicle distance information.

As for the inter-vehicle distance, the front and rear are photographed by the photographing means to obtain the front inter-vehicle distance and the rear inter-vehicle distance, respectively, and the inter-vehicle distance can be calculated by adding the distances between the photographing means. It is possible to separately acquire an image of the side of the own vehicle.

The present invention calculates the distance between front and rear vehicles in a traveling lane adjacent to the own vehicle traveling lane by a photographing means capable of photographing all directions of the vehicle, outputs this inter-vehicle distance, and collects the output inter-vehicle distance. Congestion can be predicted based on the collected inter-vehicle distance information.

When a vehicle traveling in an adjacent traveling lane becomes a blind spot in a photographed image before and after the own vehicle, the output of the inter-vehicle distance may be temporarily stopped to prevent erroneous detection of the inter-vehicle distance.

When a vehicle traveling in an adjacent driving lane becomes a blind spot in the images taken before and after the own vehicle, it is assumed that the vehicle in the blind spot is right next to the own vehicle, and the vehicle in front or behind in the photographed image. It is also possible to set the inter-vehicle distance between the vehicle on the side closer to the own vehicle and the own vehicle as the inter-vehicle distance of the adjacent vehicle.

The traffic jam prediction device according to the present invention is based on a photographing means installed in the own vehicle and capturing a front vehicle and a following rear vehicle traveling in a traveling lane adjacent to the own vehicle traveling lane, and data from the photographing means. The configuration is equipped with a calculation means for calculating the distance between the front and rear vehicles. Further, the present invention comprises a photographing means for capturing a front vehicle and a following rear vehicle traveling in a traveling lane adjacent to the own vehicle traveling lane installed in the own vehicle, and between the front and rear vehicles based on the data from the photographing means. A configuration of a traffic jam prediction device including a calculation means for obtaining a distance, a means for collecting the inter-vehicle distance and measurement position information output from the calculation means, and a means for predicting traffic congestion based on the inter-vehicle distance information for each measurement position. did.

Further, the present invention relates to a photographing means installed in front of and behind the own vehicle and directed to the front and the rear, and a distance between vehicles in front of a vehicle traveling in a traveling lane adjacent to the own vehicle lane based on an image obtained by the photographing means. It is possible to output a calculation means for calculating the distance between vehicles behind the vehicle, a clock means for obtaining the measurement time by the calculation means, a position information acquisition means mounted on the own vehicle, and the above calculation means, the clock means, and the position information acquisition means. It is also possible to have a configuration having a communication means and a server that receives data from the communication means and outputs the collected congestion information.

A mobile terminal having the photographing means, the calculation means, the clock means, and the position information acquisition means may be used. Further, it may be configured by adding a photographing means capable of photographing the side of the own vehicle. Further, the photographing means can be a photographing device having a viewing angle region of 360 degrees.

It is also possible to collect the measurement position information output from the position information acquisition device such as GPS and the inter-vehicle distance output from the calculation means, and predict the traffic congestion based on the inter-vehicle distance information for each measurement position.

According to the present invention, the distance between two vehicles in the front and rear on the adjacent lane is quickly grasped with little error during measurement, and the collected distance information is used to predict the traffic jam. Therefore, the traffic jam is predicted more accurately. It can be used for the convenience of the user.

It is an whole block block diagram explaining the traffic jam prediction apparatus which concerns on Example. It is a block diagram of the traffic jam prediction device which concerns on Example. It is a flowchart which shows the whole algorithm of the front mobile terminal of the traffic jam prediction method which concerns on Example. It is a flowchart which shows the measurement algorithm of the front mobile terminal of the same method. It is a flowchart which shows the communication algorithm of the front mobile terminal of the same method. It is a flowchart which shows the whole algorithm of the rear mobile terminal of the same method. It is a flowchart which shows the measurement algorithm of the rear mobile terminal of the same method. It is a flowchart which shows the communication algorithm of the rear mobile terminal of the same method. It is a top view of the traveling vehicle which shows the 2nd Embodiment of this invention. It is a plan perspective view of the vehicle which shows the 2nd Example. It is a plane perspective view of the vehicle which shows the 3rd Example. It is a top view of the front-rear vehicle of the third embodiment.

Hereinafter, the embodiment of the traffic jam prediction method and the traffic jam prediction device of the present invention will be described in detail with reference to the drawings. It should be noted that the embodiments shown below are a part of a suitable embodiment for carrying out the present invention, and as long as the same effect is obtained, even if a part of the configuration and the method is changed, the present invention is used. Can be considered part.

FIG. 1 is a block diagram of a traffic jam prediction method according to an embodiment, and FIG. 2 is a block diagram of a traffic jam prediction device.

As shown in these figures, in the present embodiment, the front vehicle 16 traveling in the adjacent lane 14 and the rear vehicle 18 following the front vehicle 16 as viewed from the own vehicle 12 traveling in the traveling lane 10 as a moving image by a smartphone. I'm catching it. As shown in FIG. 1, there are a front smartphone 20 mounted on the front portion of the own vehicle 12 and capable of front shooting, and a rear smartphone 22 mounted on the rear portion and capable of rear shooting, and these smartphones 20 and 22. The front image 24 and the rear image 26 are photographed, respectively.

_{As shown in FIG. 1, the inter-vehicle distance h L} between the traveling front vehicle 16 and the following rear vehicle 18 is _{the distance h 2} from the position of the photographing device 21 of the front smartphone 20 to the front vehicle 16. _{, The distance h 3} from the position of the photographing device 23 of the rear smartphone 22 to the rear vehicle 18 _{, and the distance h i i} between the smartphones 20 and 22. That is, the inter-vehicle distance h _L = h ₂ + h ₃ + h _ii . In order to obtain this, in the embodiment, the distance between vehicles in front is measured by using image processing. _{Further, the distance h ii} between the smartphones 20 and 22 may be measured in advance. Therefore, the inter-vehicle distance h _L can be calculated only from the image.

In order to obtain the inter-vehicle distance h _L = h ₂ + h ₃ + h _ii , it is necessary to collect the data of the rear (front) smartphone 22 in the front (rear) smartphone 20. Therefore, as shown in FIG. 2, the short-range communication means 30 possessed by the smartphones 20 and 22 is used. That is, the addition process is performed by the front (rear) smartphone 20. This addition is performed by a processing device 32 as a calculation unit, stored in a storage device 33 incorporating the processing device 32, and sent to, for example, a server 28 by a long-distance communication device 34 described later.

At the time of addition, the short-distance communication means 30 sends the inter-vehicle distance h ₃ measured by the rear smartphone 22 and the measured time obtained by the clock device 38 to the front smartphone 20, and the inter-vehicle distance h _{2 measured by the front smartphone 20. The inter-vehicle distance h ii} measured in advance and held in the storage device 33 is read out, the inter-vehicle distance h _L is calculated by the processing device 32, and stored in the storage device 33.

Next, the inter-vehicle distance h _L is output, and the output inter-vehicle distance h _L is collected from a plurality of vehicles 12 _n. The collection destination is, for example, the server 28. As described above, the smartphones 20 and 22 are provided with the long-distance communication device 34 for collection, and at the same time, the distance between vehicles is measured by using the position information acquisition device 36 equipped on the smartphones 20 and 22. I try to send the location information of the time. The position information acquisition device uses, for example, GPS mounted on a smartphone. Further, since the inter-vehicle distance h _L is an addition value of the front inter-vehicle distance h ₂ and the rear inter-vehicle distance h _3, it is necessary that the times at the time of addition are the same. Therefore, a clock device 38 is provided in order to obtain the measurement times of the front inter-vehicle distance h ₂ and the rear inter-vehicle distance h _3. If the measurement time difference is a certain time or more by the clock device 38, the added data is not used. The data processed in this way is sent to the server 28 by the long-distance communication device 34.

Then, as described above, the server 28 predicts the traffic congestion based on the _{collected inter-vehicle distance information {h L}.} For example, it provides information that traffic congestion will occur in the future if the period when the inter-vehicle distance is 40 m or less exceeds a certain time. The server 28 that determines this flows the traffic jam information into the transportation network created by itself, _{quickly creates the traffic jam information from the collected inter-vehicle distance information {h L} }, and quickly creates the traffic jam information, such as a transportation company, a bus company, a taxi company, or a highway company. The user 40 pays the usage fee 42 and can utilize the traffic jam information 44.

The specific processing procedure will be described below with reference to FIGS. 3 to 8.
FIG. 3 shows the overall processing of the front smartphone 20. First, the front smartphone measurement algorithm starts (S100). As shown in FIG. 4, this measurement algorithm captures an image using the imaging device 21 (S101). After that, the presence or absence of the vehicle in front 16 is confirmed (S102), and it is determined whether or not the recognized vehicle is in the adjacent lane 14 (S103). If it is not reflected, the process is completed, and if it is reflected, the distance is calculated using image processing (S104). As shown in FIG. 3, when the measurement is completed, the information is stored in the storage device 33 as the distance between vehicles ahead (S110). _{If there is no information on the distance h 2} in front of the vehicle, the work is terminated with no information on traffic congestion at that point (S170), and if there is information, the process proceeds to the next front smartphone communication algorithm (S120).

As shown in FIG. 5, it is checked whether or not the short-range communication means 30 as the communication means can communicate with the other party's smartphone 22 (S121), the work is completed if it is impossible, and the measured inter-vehicle distance h if possible. ₂ and the measurement time of the other party's smartphone 22 are received (S122). _{Then, it is confirmed whether or not the time difference when measuring the inter-vehicle distances h 2} and h ₃ of the front and rear smartphones 20 and 22 is within a certain time (S123), and if it is within a certain time, it is stored in the storage device 33, and if not, it is stored. Reset to exit. This is to determine whether or not the inter-vehicle distances h ₂ and h _{3 at the time of measurement are correct.} When this is completed, the process returns to the overall alcoholism, and the front-rear inter-vehicle distances h ₂ and h ₃ are calculated (S130). _{The distance h i i} between the photographing devices 21 and 23 is added to obtain the inter-vehicle distance h _L, and it is determined whether this is 40 m or more or less than the specified value (S140). This is based on the research result that if the inter-vehicle distance h _L is less than 40 m, congestion will start in the future (Shincho Sensho Congestion Studies, Katsuhiro Nishinari, P48-). Of course, you can change this number. In order to exclude special situations such as when the _{inter-vehicle distance h L} is momentarily shortened regardless of the degree of traffic congestion, _{it is checked whether the measured inter-vehicle distance h L} is less than the specified value for 3 minutes. Judgment (S150). Of course, you can change this time. If the inter-vehicle distance h _L continues to be less than the specified value for a certain period of time or longer, the point is considered to be a sign of traffic congestion or is stored in the storage device 33 as being in a traffic jam (S160).

As can be seen from FIG. 6, the overall algorithm of the rear smartphone 22 first implements the measurement algorithm of the rear smartphone 22 (S200). This algorithm works the same as before. That is, as shown in FIG. 7, an image is captured using the photographing device 23 (S201). After that, the presence or absence of the rear vehicle 18 is confirmed (S202), and it is determined whether or not the recognized vehicle is in the adjacent lane 14 (S203). If it is not reflected, the process is completed, and if it is reflected, the distance is calculated using image processing (S204). When the measurement is completed, the information is stored in the storage device 33 as the distance between vehicles behind (S210). Returning to the overall algorithm of the rear smartphone 22 side in FIG. 6, if there is no information of the rear vehicle distance h _3, exit work as information talk congestion at that point, the process proceeds to the next rear smartphone communication algorithm if any information (S220). It is checked whether the short-range communication means 30 as the communication means can communicate with the front smartphone 20 which is the other party (S221), and if it is impossible, the work is completed, and if possible, the measured rear vehicle-to-vehicle distance h. ₃ and the time measured by the clock device 38 are transmitted (S222), and the process ends.

In this way, the time lag when measuring the front-rear inter-vehicle distances h ₂ and h ₃ of the front-rear smartphones 20 and 22 is confirmed, and the front-rear inter-vehicle distances h ₂ and h ₃ are calculated. _{The distance h i i} between the photographing devices 21 and 23 is added to obtain the inter-vehicle distance h _L, and it is determined whether this is equal to or less than the specified value. If the measured inter-vehicle distance h _L is less than the specified value, the point is considered to be a sign of traffic congestion or is stored in the storage device 33 as being in a traffic jam.

This result can be sent to the server 28 through the long-distance communication device 34, for example, the server 28 collects data, and can be used to predict traffic congestion based _{on the collected inter-vehicle distance information {h L}.} For example, since a certain amount of information that the distance between vehicles is 40 m or less is collected, information that traffic congestion will occur in the future is provided. The server 28 that determines this flows the traffic jam information into the transportation network created by itself, _{quickly creates the traffic jam information from the collected inter-vehicle distance information {h L} }, and quickly creates the traffic jam information, such as a transportation company, a bus company, a taxi company, or a highway company. The user 40 pays the usage fee 42 and can utilize the traffic jam information 44.

As described above, according to the present embodiment, an image is obtained by projecting the front and rear with an in-vehicle photographing device, the distance between the front vehicle and the distance between the rear vehicles are obtained from the image, and the distance between the photographing devices is also added to obtain the target adjacent vehicle. The distance between two cars on the line can be calculated. If this is linked with location information and time information and sent to a server by communication means, and the sent data is collected, it is possible to reflect in the traffic information that traffic congestion will occur in the future. By utilizing this data by users, a significant improvement effect can be expected. At this time, when measuring the front and rear vehicles in the adjacent lane, anyone who has a mobile terminal such as a smartphone equipped with a shooting means, a position information acquisition means, a clock means, and a communication means can easily and at low cost. It can provide predictive material for traffic congestion.

In the above embodiment, the inter-vehicle distance was measured using the smartphones 20 and 22, but in addition to attaching the photographing devices 21 and 23 in the front and rear, as shown in FIG. 9, the side smartphone 46 for viewing the side is used. It may be attached. The side smartphone 46 is a device having the same function as the rear smartphone 22. Of course, if the device has the same function, it can be replaced with the side smartphone 46. In this way, as shown in FIG. 10, when vehicles are lined up in the adjacent lane 14, the speeds of the front vehicle 16 and the rear vehicle 18 following the speed increase, and when the vehicle is running in parallel with the own vehicle 12, the vehicle is rearward. The vehicle 18 enters the blind spot of the front-rear photographing devices 21 and 23. At this time, since the rear vehicle 18 can be photographed by the presence of the side smartphone 46, the correct inter-vehicle distance h _L can be measured. When measured by this side smartphone 46, the output of the inter-vehicle distance is temporarily stopped when the vehicle traveling in the adjacent lane 14 becomes a blind spot in the photographed images in front of and behind the own vehicle even as an adjacent traveling lane. , Try to prevent false detection of inter-vehicle distance. Further, when a vehicle traveling in an adjacent traveling lane becomes a blind spot in a photographed image in front of and behind the own vehicle, it is assumed that the vehicle 18 in the blind spot is directly beside the own vehicle 12, and the front in the photographed image. Alternatively, the inter-vehicle distance between the own vehicle and the vehicle on the side of the rear vehicle that is closer to the own vehicle 12 may be set as the inter-vehicle distance of the adjacent vehicle.

Further, as shown in FIG. 11, a 360-degree camera 48 is installed inside or outside the own vehicle 12, images the front image 24 and the rear image 26 are captured, and image processing is performed using a calculation device in the image. The distance between the front vehicle 16 and the rear vehicle 18 may be obtained from the size and position. According to this, as shown in FIG. 12, when a vehicle in the adjacent lane is on the side of the own vehicle 12, the front-rear photographing devices 21 and 23 correspond to the blind spot of the photographing device, but the 360-degree camera 48 shoots in all directions. becomes possible, it can be measured more accurate vehicle distance h _t, and since the imaging apparatus can imaging by simply installing a single, there is a cost reduction effect.

In the embodiment, a smartphone having a shooting function, a position information acquisition function, a clock function, and a communication function is used, but it can be realized by a means having a single function.

According to the present invention, traffic congestion can be predicted from the distance between vehicles, and anyone can easily use it and provide it to a server user.

10 ... own vehicle driving lane, 12 ... own vehicle, 14 ... adjacent lane (adjacent driving lane), 16 ... front vehicle, 18 ... rear vehicle, 20 ... front smartphone, 22 ... rear smartphone, 24 ... front image, 26 ... rear image, 28 ... server, 30 ... short-range communication means, 32 ... processing device, 33 ... storage device, 34 ... long-range communication device, 36 ... position information Acquisition device, 38 ... Clock device, 40 ... User, 42 ... Usage fee, 44 ... Congestion information, 46 ... Side smartphone, 48 ... 360 degree camera.

Claims (14)

When predicting traffic congestion, the front and rear are photographed by the photographing means mounted on the own vehicle, and the inter-vehicle distance between the front vehicle traveling in the traveling lane adjacent to the own vehicle traveling lane and the following rear vehicle is used. A traffic jam prediction method characterized by this. The inter-vehicle distance between the front vehicle traveling in the traveling lane adjacent to the own vehicle traveling lane and the following rear vehicle is calculated from the captured images before and after the vehicle, and this inter-vehicle distance is output and the output inter-vehicle distance is output. A traffic jam prediction method characterized by collecting images and predicting traffic jams based on the collected inter-vehicle distance information. The claim is characterized in that the inter-vehicle distance can be calculated by photographing the front and the rear respectively by a photographing means, obtaining the front inter-vehicle distance and the rear inter-vehicle distance, and adding the distances between the photographing means to calculate the inter-vehicle distance. Congestion prediction method according to 1. The traffic congestion prediction method according to claim 1, wherein an image of the side of the own vehicle can be separately acquired. The distance between the front and rear vehicles in the traveling lane adjacent to the own vehicle traveling lane is calculated by a photographing means capable of photographing all directions of the vehicle, this inter-vehicle distance is output, the output inter-vehicle distance is collected, and the collected inter-vehicle distance is collected. A traffic jam prediction method characterized by predicting traffic jams based on distance information. The claim is characterized in that when a vehicle traveling in an adjacent traveling lane becomes a blind spot in a photographed image before and after the own vehicle, the output of the inter-vehicle distance is temporarily stopped to prevent erroneous detection of the inter-vehicle distance. Congestion prediction method according to 1. When a vehicle traveling in an adjacent driving lane becomes a blind spot in the images taken before and after the own vehicle, it is assumed that the vehicle in the blind spot is right next to the own vehicle, and the vehicle in front or behind in the photographed image. The traffic congestion prediction method according to claim 1, wherein the distance between the vehicle on the side closer to the own vehicle and the own vehicle is set as the distance between adjacent vehicles. A means of photographing the front vehicle and the following rear vehicle that are installed in the own vehicle and are traveling in the traveling lane adjacent to the own vehicle traveling lane.
A calculation means for obtaining the distance between the front and rear vehicles based on the data from the photographing means, and
Vehicle congestion prediction device equipped with. A means of photographing the front vehicle and the following rear vehicle that are installed in the own vehicle and are traveling in the traveling lane adjacent to the own vehicle traveling lane.
A calculation means for obtaining the distance between front and rear vehicles based on the data from the photographing means, and
A means for collecting the inter-vehicle distance and measurement position information output from the calculation means and predicting traffic congestion based on the inter-vehicle distance information for each measurement position.
A traffic jam prediction device characterized by being equipped with. Shooting means installed in front of and behind the vehicle and directed forward and backward,
A calculation means for calculating the front-to-vehicle distance and the following rear-to-vehicle distance of a vehicle traveling in a traveling lane adjacent to the own vehicle lane based on the image obtained by this photographing means.
A clock means for obtaining the measurement time by this calculation means, and
The location information acquisition means installed in the own vehicle and
A communication means capable of outputting the above-mentioned calculation means, clock means, and position information acquisition means, and
A server that receives data from this communication means and outputs the collected traffic jam information,
A traffic jam prediction device characterized by having. The traffic congestion prediction device according to claim 8, wherein a mobile terminal having the photographing means, the calculation means, the clock means, and the position information acquisition means is used. The traffic jam prediction device according to claim 8 or 9, wherein a photographing means capable of photographing the side of the own vehicle is added. The traffic congestion prediction device according to claim 8, wherein the photographing means is a photographing device having a viewing angle region of 360 degrees. The traffic jam prediction according to claim 9 or 10, which collects the measurement position information output from the position information acquisition device and the inter-vehicle distance output from the calculation means, and predicts the traffic jam information based on the inter-vehicle distance information for each measurement position. Device.

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