JP2021051423A - Road information distribution system, road information distribution device, and road information distribution program - Google Patents

Abstract

To provide a road information distribution system for collecting detection information from a plurality of vehicles and distributing road information indicating a road state to the respective vehicles based on detection information.SOLUTION: A road information distribution system includes: an on-vehicle terminal for acquiring detection information; and a management device for distributing road information based on detection information. The on-vehicle terminal includes: first sensor equipment for imaging a front side and/or a rear side of a mounting vehicle with the on-vehicle terminal mounted thereon, and then acquiring an image; second sensor equipment for acquiring first position information indicating a position of the mounting vehicle; and a detection information acquisition section for acquiring detection information where an image is associated with the first position information. The management device includes: a storage section for storing detection information; an image recognition section for performing image recognition processing with respect to an image with which the first position information is associated, based on the second position information indicating a position of a vehicle of a distribution destination; and a determination section for generating road information. The determination section estimates an inter-vehicle distance and also generates road information indicating a congestion degree of vehicles.SELECTED DRAWING: Figure 1

Description

The present invention relates to a technique for distributing road information.

Conventionally, there is a system that acquires image data and position information from a plurality of vehicles and distributes road information to each vehicle based on the acquired image data and position information. In each vehicle, for example, the congestion status of the road can be grasped by referring to the distributed road information.

Japanese Unexamined Patent Publication No. 2014-191578 Japanese Unexamined Patent Publication No. 2007-071579

Provided is a road information distribution system that collects detection information from a plurality of vehicles and distributes road information indicating road conditions to each vehicle based on the detection information.

The road information distribution system of the embodiment is a road information distribution system including an in-vehicle terminal that acquires detection information and a management device that can communicate with the in-vehicle terminal and distributes road information based on the detection information. The in-vehicle terminal includes a first sensor device that captures an image of the front and / or rear of the on-board vehicle on which the in-vehicle terminal is mounted and acquires an image, and a second sensor device that acquires first position information indicating the position of the on-board vehicle. , A detection information acquisition unit for acquiring detection information in which an image acquired at a predetermined time and a first position information acquired at a predetermined time are linked is provided. The management device indicates a position within a predetermined range regarding the position of the vehicle to which the road information is distributed, based on the storage unit that stores the detection information in advance and the second position information indicating the position of the vehicle to which the road information is distributed. It includes an image recognition unit that executes an image recognition process for an image associated with the first position information, and a determination unit that generates road information regarding a predetermined range based on a determination based on the result of the image recognition process. Then, the determination unit estimates the inter-vehicle distance based on the vehicle included in the image, and generates road information indicating the degree of congestion of the vehicle.

It is a network block diagram of the road information distribution system of 1st Embodiment. It is a functional block diagram of the road information distribution system of 1st Embodiment.

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

(First Embodiment)
FIG. 1 is a network configuration diagram of the road information distribution system of the present embodiment. The road information distribution system includes an in-vehicle terminal 100 and a management device 200 (corresponding to a road information distribution device). The in-vehicle terminal 100 and the management device 200 are wirelessly connected via a network such as an IP network. The in-vehicle terminal 100 is mounted on a vehicle such as an automobile or a motorized bicycle. The management device 200 is provided in, for example, a road traffic control center that manages road traffic conditions. The in-vehicle terminal 100 acquires detection information about a vehicle on which the in-vehicle terminal 100 is mounted (hereinafter referred to as an mounted vehicle) and transmits the detection information to the management device 200. The detection information includes vehicle position information, image data taken by a camera mounted on the vehicle, and the like, as will be described later.

The detection information acquired by the in-vehicle terminal 100 is transmitted to the management device 200 from a plurality of mounted vehicles. The management device 200 can accumulate the detection information received from each mounted vehicle. The management device 200 executes analysis processing based on the detection information received from each mounted vehicle, and generates road information for grasping the road condition (traffic condition) on which each mounted vehicle travels. The management device 200 distributes road information to each on-board vehicle. In other words, the on-board vehicle is a probe car that functions as a sensor that acquires detection information for generating road information.

FIG. 2 is a functional block diagram of the road information distribution system. The in-vehicle terminal 100 includes a control unit 110, a sensor unit 120, a storage unit 130, a communication unit 140, and an output unit 150. The storage unit 130 stores various information. The communication unit 140 controls communication with the management device 200.

The control unit 110 includes a detection information acquisition unit 111. The detection information acquisition unit 111 acquires the detection information regarding the mounted vehicle according to the acquisition setting information described later. The detection information acquisition unit 111 collects the information output from the sensor unit 120 as the detection information. In addition, the detection information acquisition unit 111 can also collect information detected by a device already mounted on the mounted vehicle as detection information. For example, the detection information acquisition unit 111 collects information on ON / OFF of the brake pedal, information on ON / OFF of the wiper, information on the temperature detected by the outside air temperature sensor, information on running speed, and the like as detection information.

The sensor unit 120 includes a camera 121 (corresponding to the first sensor device) and a GPS (Global Positioning System) sensor 122 (corresponding to the second sensor device). The camera 121 is provided so as to be able to photograph the front and / or the rear of the mounted vehicle. A plurality of cameras 121 can be provided. The camera 121 generates image data by shooting. For example, the camera 121 is a visible light camera, a near infrared camera, an infrared camera, or the like. The GPS sensor 122 acquires vehicle position information (corresponding to the first position information). The image data and the position information are output to the detection information acquisition unit 111 as detection information.

The output unit 150 transmits the road information provided by the management device 200 to the occupants of the mounted vehicle by each output device. The output unit 150 has, for example, a display (display unit) and a speaker, displays road information provided by the management device 200, and outputs sound based on the road information.

The storage unit 130 stores acquisition setting information for the detection information acquisition unit 111 to acquire predetermined detection information. The acquisition setting information includes acquisition condition information and designated information corresponding to the acquisition condition information. The acquisition condition information is information that defines the conditions for acquiring the detection information. The designated information is information that defines the detection information to be acquired. The acquisition condition information and the designated information are defined by the detection information, respectively.

The process of acquiring the detection information on the in-vehicle terminal 100 will be described. When the detection information specified in the acquisition condition information is detected, the detection information acquisition unit 111 acquires the detection information and the detection information specified in the designated information. The detection information acquisition unit 111 acquires image data at least at a predetermined time (detection time described later) and position information at a predetermined time based on the acquisition setting information.

For example, when "position information [XXX (position coordinates indicating position information)]" is set as a condition in the acquisition condition information, "image data" and "time" are set in the designated information. In this case, when the GPS sensor 122 acquires the position information [XXX], the camera 121 takes a picture and generates image data. At this time, the timer (not shown) measures the time, and the time when the GPS sensor 122 acquires the position information [XXX], in other words, the shooting time by the camera 121 can be grasped. Here, the time at which the position information is acquired and the shooting time are referred to as detection times. In addition, the position information indicates the shooting location of the image. In this way, the detection information acquisition unit 111 can acquire the position information of the predetermined point, the image data, and the detection time in association with each other when the mounted vehicle reaches the predetermined point.

In addition, the geographic range using the location information may be set in the acquisition condition information. For example, the range can be set in the acquisition condition information by using the position information of the A point, the position information of the B point, and the position information of the C point. At this time, when the mounted vehicle enters the range surrounded by the points A to C, the detection information acquisition unit 111 can acquire various detection information by the above-mentioned method.

If the location information set as the acquisition condition information includes location information such as a point with heavy traffic (prone to congestion) such as an intersection or a branch point, an accident occurrence point, or an accident frequent occurrence point, the acquired detection information is obtained. Based on the above, it becomes easier for the occupants of the vehicle to provide information that should be noted from the management device 200.

Further, when "time [X hours X minutes]" is set as a condition in the acquisition condition information, "image data" and "position information" are set in the designated information. In this case, when the time grasped by the timer reaches X hours and X minutes, the camera 121 takes a picture to generate image data, and the GPS 122 acquires the position information. In this way, the detection information acquisition unit 111 can acquire the time (that is, the detection time), the position information, and the image data in association with each other when the predetermined time is reached. By setting the time in the acquisition condition information at each predetermined time, the detection information acquisition unit 111 can acquire the position information, the image data, and the detection time at each predetermined time.

The information acquired by the detection information acquisition unit 111 is transmitted to the management device 200 and stored in the storage device 230 (described later) of the management device 200.

Further, the acquisition setting information is preset in the management device 200 and distributed to the in-vehicle terminal 100. Further, the acquisition setting information can be set in advance on the in-vehicle terminal 100 side. The acquisition setting information can be arbitrarily added or changed. The acquired detection information is transmitted to the management device 200 via the communication unit 140, and is stored in the storage device 230, which will be described later. In other words, the management device 200 collects the detection information output from the in-vehicle terminal 100.

In the above description, the image data, the position information, and the detection time have been used, but the detection information acquisition unit 111 determines the detection information detected by other devices already installed in the vehicle. It can be obtained under the conditions of. The above-mentioned acquisition setting information is an example, and it is sufficient that the detection information acquisition unit 111 can acquire the predetermined detection information specified by the predetermined conditions.

The management device 200 includes a communication device 210, a control device 220, and a storage device 230. The communication device 210 controls communication with the in-vehicle terminal 100. The storage device 230 stores the detection information received from the in-vehicle terminal 100. The control device 220 has a determination unit 221 and a road information distribution unit 222. The determination unit 221 executes various determination processes described later and generates road information as a result of the determination processes. The road information distribution unit 222 distributes the generated road information.

The determination unit 221 has an image recognition unit 2211 and a determination unit 2212. The image recognition unit 2211 executes an image recognition process on the image data stored in the storage device 230 as detection information. The determination unit 2212 executes a determination process based on the result of the image recognition process and generates various road information. The determination unit 221 executes a lane congestion degree determination process, a road surface condition determination process, and a pedestrian determination process (described later). Examples of road information include lane congestion information, road surface condition information, and pedestrian information.

The lane congestion degree determination process will be described. The lane congestion degree determination process is a process for determining the congestion degree of a vehicle for each lane. The lane congestion degree determination process includes a congestion degree determination process and a lane recognition process.

First, the congestion degree determination process will be described. The image recognition unit 2211 executes an image recognition process on the image data collected as the detection information. For example, the image recognition unit 2211 executes the image recognition process based on the vehicle detection dictionary for recognizing the vehicle in front (hereinafter referred to as the vehicle detection dictionary). For example, a vehicle detection dictionary contains feature quantities that describe vehicle features such as vehicle contours, window frames, bumpers, and tires. The vehicle detection dictionary is stored in, for example, the storage device 230.

The image recognition unit 2211 executes the image recognition process by matching the feature amount image obtained by performing the feature amount extraction process on the image collected from the mounted vehicle with the vehicle detection dictionary. As a result, the image recognition unit 2211 recognizes the area occupied by the characteristic portion of the vehicle in front in the image. The determination unit 2212 estimates the distance between the mounted vehicle and the vehicle in front of the mounted vehicle, that is, the inter-vehicle distance, based on the size of the area occupied by the characteristic portion of the vehicle in front in the image or the position where the vehicle is installed on the road surface. To do. In the same way, the inter-vehicle distance between the mounted vehicle and the vehicle behind the mounted vehicle can be estimated. The method of estimating the inter-vehicle distance may be another existing method.

For example, the determination unit 2212 can determine that the shorter the estimated inter-vehicle distance, the higher the degree of congestion. The determination unit 2212 can determine that the longer the estimated inter-vehicle distance, the lower the degree of congestion.

Next, the lane recognition process will be described. The image recognition unit 2211 executes an image recognition process on the image data collected as the detection information. For example, the image recognition unit 2211 is an image based on a line segment detection process for recognizing a lane, conditions such as the width and color of the lane boundary, conditions related to the lane width, and a template image (hereinafter referred to as a lane template image). Execute recognition processing. The lane boundary condition is stored in, for example, the storage device 230.

Here, a lane boundary line that defines a boundary between lanes is drawn on the road. Therefore, the position of the lane boundary line in the image taken by the camera 121 differs depending on the lane in which the mounted vehicle is located. For example, when the on-board vehicle is located in the left lane, the lane boundary is located on the right side in the image of the front of the vehicle. For example, when the on-board vehicle is located in the right lane, the lane boundary is located on the left side in the image of the front of the vehicle. For example, when the mounted vehicle is located in the central lane, the lane boundaries are located on both the left and right sides in the image of the front of the vehicle. Therefore, lane boundary conditions are prepared for each of the above-mentioned images.

The image recognition unit 2211 executes the image recognition process by matching the image collected from the mounted vehicle, the result of performing the line segment detection process on the image, and the condition of the lane boundary line. As a result, the determination unit 2212 grasps the position of the lane boundary line in the image collected from the mounted vehicle. Then, the determination unit 2212 can determine the lane in which the mounted vehicle is located among the plurality of lanes based on the position of the lane boundary line. The method of recognizing a lane may be another existing method.

By grasping the lane as well as the degree of congestion as described above, the degree of congestion for each lane can be determined. The degree of congestion for each lane is distributed to the in-vehicle terminal 100 according to the request information transmitted from the in-vehicle terminal 100 as described later. In the congestion degree determination process, the traveling speed may be taken into consideration. For example, when information on the traveling speed of the mounted vehicle is stored in the storage device 230 as detection information together with the image data, the determination unit 2212 can determine the degree of congestion in consideration of the traveling speed. Thereby, the degree of congestion can be determined based on both the inter-vehicle distance and the traveling speed, such as when the traveling speed is high even if the inter-vehicle distance is short, or when the traveling speed is slow even if the inter-vehicle distance is long. Similarly, when the information regarding the ON / OFF of the brake pedal is stored in the storage device 230 as the detection information, the determination unit 2212 can determine the degree of congestion in consideration of the ON / OFF of the brake pedal. For example, when the brake pedal is turned on for a long time or when the brake pedal is turned on many times, it can be determined that the degree of congestion is high.

The road surface condition determination process will be described. The road surface condition determination process is a process for determining the road surface condition of the road. Examples of the road surface condition include a snow condition and a road surface freezing condition. The road surface condition determination process includes a snow cover condition determination process and a frozen state determination process.

First, the snow cover state determination process will be described. The image recognition unit 2211 executes an image recognition process on the image data collected as the detection information. For example, the image recognition unit 2211 executes the image recognition process based on the template image for recognizing the road surface state (hereinafter, referred to as the road surface state template image). The road surface state template image is stored in, for example, the storage device 230.

Here, in the road with snow, the proportion of white color increases due to snow as compared with the road without snow (without snow). Therefore, when comparing the image of the road with snow and the image of the road with no snow, the image of the road with snow has more white pixels (area showing white). Therefore, in the road surface condition template image, an image of the road when there is no snow is prepared.

The image recognition unit 2211 executes the image recognition process by searching for and comparing the images collected from the mounted vehicle from the road surface template image. As a result, the determination unit 2212 can grasp the region changed to white due to the snow cover from the difference between the image collected from the mounted vehicle and the road surface template image. The determination unit 2212 can determine the presence or absence of snow cover based on the region that has changed to white.

Here, since snow accumulates upward from the road surface (in the direction away from the road surface), there is a space without snow above the snow-covered area on the road surface. The space without snow is not white because there is no color development due to snow. Therefore, the determination unit 2212 can estimate the snow depth (for example, the snow depth) based on the white regions detected in order from the bottom in the image taken at the time of snow cover. Here, the snow depth can be expressed in units such as cm. In the above description, the snow is colored white, but by presetting the color developed by the snow, the preset color region is detected as the snow-covered region, and the snow is covered. The depth can be determined. In this way, the determination unit 211 generates snow cover information as a result of the snow cover state determination process. The method for estimating the depth of snow cover may be another existing method.

Next, the frozen state determination process will be described. Frozen road surfaces develop a darker color than non-frozen road surfaces. Therefore, as the road surface template image, an image of a non-frozen road surface is prepared.

The image recognition unit 2211 executes the image recognition process by matching the image collected from the mounted vehicle with the road surface template image. As a result, the determination unit 2212 can grasp the region where the color has changed due to freezing from the difference between the image collected from the mounted vehicle and the road surface template image. At this time, the determination unit 2212 determines (estimates) that the road surface has frozen when the pixel value changes by a predetermined value or more in the region where the color has changed darkly. As a result, the image recognition unit 2211 can determine whether or not the road surface is frozen. In this way, the determination unit 211 generates freeze information as a result of the freeze state determination process. The method for determining the presence or absence of freezing may be another existing method.

As the road surface template image, an image taken at a point indicated by predetermined position information in advance when the road surface is not affected by snow or freezing is prepared. Position information indicating the shooting location is associated with the road surface template image. For example, the image recognition unit 2211 can execute the road surface condition determination process when the position information associated with the road surface template image and the position information associated with the image data obtained from the mounted vehicle match. For example, the road surface template image and the position information associated with the road surface template image may be collected in advance from the mounted vehicle. The road surface template image and the position information associated with the road surface template image are stored in, for example, the storage device 230.

In the road surface condition determination process, information on the temperature detected by the outside air temperature sensor (air temperature information) and information on the ON / OFF of the wiper may be taken into consideration. When the temperature information is stored in the storage device 230 as the detection information together with the image data, the determination unit 2212 can make a determination in consideration of the temperature in addition to the result of the image recognition. For example, when the air temperature is equal to or lower than a predetermined value, the determination unit 2212 additionally determines that the road surface is frozen based on the result of image recognition. Similarly, the determination unit 2212 can additionally determine that there is snow. Further, when the information on the ON / OFF of the wiper is stored in the storage device 230 as the detection information together with the image data, the determination unit 2212 makes a determination in consideration of the ON / OFF of the wiper in addition to the result of the image recognition. Can be done. For example, when the wiper is ON, the determination unit 2212 can determine that it is snowing, and can additionally determine that there is snow based on the result of image recognition.

The pedestrian determination process will be described. The image recognition unit 2211 executes a process for recognizing a person (hereinafter referred to as a pedestrian) existing around the mounted vehicle based on the image data collected as the detection information. For example, the image recognition unit 2211 recognizes a pedestrian region included in a captured image by using a person detection dictionary (referred to as a person detection dictionary) including feature points and patterns learned in advance. As a result, the determination unit 2212 estimates (determines) the position and number of pedestrians. Similarly, the image recognition unit 2211 can perform face recognition processing on the recognized pedestrian face using a face detection dictionary (referred to as a face detection dictionary). As a result, the determination unit 2212 estimates (determines) the characteristics of the pedestrian such as the sex, age group, and facial expression of the photographed pedestrian. An existing method can be applied to the process for grasping the number of pedestrians captured in the above-mentioned image and the face recognition process.

The determination unit 2212 can determine the degree of congestion of pedestrians around the mounted vehicle by grasping the number of pedestrians existing around the mounted vehicle (may include the position of the pedestrian). it can. For example, when the number of people existing around the mounted vehicle exceeds a predetermined value, it is determined that the degree of congestion of pedestrians is high. The determination unit 2212 determines that the greater the number of pedestrians, the higher the degree of congestion of the pedestrians. As the number of pedestrians decreases, the determination unit 2212 determines that the degree of congestion of pedestrians is low.

In addition to the degree of congestion of pedestrians, it is also possible to make a determination using the result of face recognition processing. For example, as a result of face recognition processing, when it is determined that the proportion of women among pedestrians is high and the degree of congestion of pedestrians is high, it means that an event for women is being held around the vehicle. , It can be predicted that there are tourist destinations for women. Similarly, as a result of face recognition processing, when it is determined that the proportion of men among pedestrians is high and the degree of congestion of pedestrians is high, an event for men is being held around the onboard vehicle. And it can be predicted that there are tourist spots for men. The information determined regarding the pedestrians existing around the mounted vehicle is distributed to the in-vehicle terminal 100 in response to the request information transmitted from the in-vehicle terminal 100 as described later.

The image recognition unit 2211 can execute the above-mentioned various determination processes (lane congestion degree determination process, road surface condition determination process, pedestrian determination process) on each image data obtained from the plurality of in-vehicle terminals 100. The management device 200 distributes the results of various determination processes as road information. When the request information is input, the management device 200 executes various determination processes. The determination process executed according to the request information is preset.

Here, the request information is information for requesting road information, and is transmitted from the in-vehicle terminal 100. At this time, the in-vehicle terminal 100 transmits the position information (corresponding to the second position information) to the management device 200 together with the request information. For example, the position information is output from the GPS sensor 122 when the mounted vehicle reaches a predetermined position, and is transmitted to the management device 200. The management device 200 executes various determination processes based on the position information acquired (input) together with the request information.

For example, the determination unit 221 executes the lane congestion degree determination process based on the position information acquired together with the request information. The determination unit 221 executes the lane congestion degree determination process based on the image data taken in advance within a predetermined road range based on the position information acquired together with the request information. Specifically, the determination unit 221 reads the image data associated with the position information within the predetermined road range based on the acquired position information from the storage device 230, and executes the lane congestion degree determination process. The road information distribution unit 222 distributes the result of the lane congestion degree determination process (lane congestion degree information) to the in-vehicle terminal 100 as road information.

The distributed lane congestion degree information is transmitted to the occupants (users) of the on-board vehicle by the output unit 150 of the in-vehicle terminal 100. For example, when the in-vehicle terminal 100 has a display for displaying a map, lane congestion degree information in a predetermined road range can be reflected and displayed on the map by color coding according to the congestion degree. Further, when the in-vehicle terminal 100 has a speaker, lane congestion degree information can be output by voice. As a result, the user can grasp the degree of congestion for each lane in a predetermined range and select a lane with a low degree of congestion.

For example, the determination unit 221 executes the road surface condition determination process based on the position information acquired together with the request information. The determination unit 221 executes the road surface condition determination process based on the image data taken in advance within a predetermined road range based on the position information acquired together with the request information. Specifically, the determination unit 221 reads the image data associated with the position information within the predetermined road range based on the acquired position information from the storage device 230, and executes the road surface condition determination process. The road information distribution unit 222 distributes the result of the road surface condition determination process (road surface condition information) to the in-vehicle terminal 100 as road information. It is also possible to execute only the snow cover state determination process or only the frozen state determination process.

The distributed road surface condition information is transmitted to the occupants (users) of the on-board vehicle by the output unit 150 of the in-vehicle terminal 100. For example, when the in-vehicle terminal 100 has a display for displaying a map, the road surface condition information of a predetermined road range can be reflected and displayed on the map. Further, when the in-vehicle terminal 100 has a speaker, the road surface condition information may be output by voice. As a result, the user can grasp the snow depth of the road surface and the presence or absence of freezing of the road surface in a predetermined road range, and can avoid the road in the road surface condition which adversely affects the traveling.

For example, the determination unit 221 executes the pedestrian determination process based on the position information acquired together with the request information. The determination unit 221 executes the pedestrian determination process based on the image data taken in advance within a predetermined road range based on the position information acquired together with the request information. Specifically, the determination unit 221 reads the image data associated with the position information within the predetermined road range based on the acquired position information from the storage device 230, and executes the pedestrian determination process. The road information distribution unit 222 distributes the result of the pedestrian determination process (pedestrian information) to the in-vehicle terminal 100 as road information.

The distributed pedestrian information is transmitted to the occupants (users) of the on-board vehicle by the output unit 150 of the in-vehicle terminal 100. For example, when the in-vehicle terminal 100 has a display for displaying a map, pedestrian information in a predetermined road range can be reflected and displayed on the map. Further, when the in-vehicle terminal 100 has a speaker, pedestrian information may be output by voice. The user can grasp the degree of congestion of pedestrians and the characteristics of pedestrians by referring to the information about pedestrians within a predetermined road range. As a result, the user can predict a tourist spot located near a predetermined road range or an event held in the vicinity of a predetermined road range from the characteristics of the pedestrian at a point where the pedestrian is highly congested. can do. In addition, the user can reduce the risk of personal injury by moving away from a point where pedestrians are highly congested.

A predetermined road range based on the acquired position information can be set in advance. The predetermined road range based on the acquired position information can be set to, for example, a range in which the on-board vehicle that has transmitted the request information can travel. Further, when the request information is transmitted from the in-vehicle terminal 100, the position information indicating the departure place of the mounted vehicle and the position information indicating the destination can also be transmitted. In this case, various determination processes can be executed based on the image data taken on the route expected based on the position information indicating the departure place and the position information indicating the destination.

The determination unit 221 can also execute various determination processes in real time based on the detection information collected from the in-vehicle terminal 100. In this case, the road information distribution unit 222 distributes the results of various determination processes when the position information is input together with the request information.

According to the road information distribution system of the present embodiment, since the management device 200 executes the image recognition process having a large processing load, it is not necessary to install an advanced device for performing the image recognition process for each vehicle. Therefore, the cost can be suppressed as compared with the case where the image recognition processing is performed on the vehicle side.

Further, according to the road information distribution system of the present embodiment, by executing various determination processes based on one type of data called image data, the degree of congestion for each lane, the condition of the road surface (snow cover, freezing), and pedestrians. It is possible to extract a plurality of different information such as the degree of congestion and characteristics of the vehicle at once.

Although the road information distribution system of the embodiment has been described above, the in-vehicle terminal 100 and the management device 200 have not only the above-mentioned hardware configurations but also operation inputs of a memory (main storage device), a mouse, a keyboard, a touch panel, a scanner, and the like. A means, an output means such as a printer, an auxiliary storage device (hardware, etc.), and the like can be provided.

Further, each function of the present invention can be realized by a program, a computer program prepared in advance for realizing each function is stored in the auxiliary storage device, and a control unit such as a CPU is stored in the auxiliary storage device. The program is read into the main storage device, and the control unit executes the program read into the main storage device so that the in-vehicle terminal 100 and the management device 200 can operate the functions of each part of the present invention. On the other hand, each function of the present invention can be configured by an individual control device, and a plurality of control devices can be directly connected or connected via a network to form an IVR device.

Further, the above program can be provided to a computer in a state of being recorded on a computer-readable recording medium. Computer-readable recording media include optical discs such as CD-ROMs, phase-changing optical discs such as DVD-ROMs, magneto-optical disks such as MO (Magnet Optical) and MD (Mini Disk), floppy (registered trademark) disks, and the like. Examples include magnetic disks such as removable hard disks, compact flash (registered trademark), smart media, SD memory cards, and memory cards such as memory sticks. Further, a hardware device such as an integrated circuit (IC chip or the like) specially designed and configured for the purpose of the present invention is also included as a recording medium.

Although the embodiment of the present invention has been described, the embodiment is presented as an example and is not intended to limit the scope of the invention. This novel embodiment can be implemented in various other embodiments, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the scope of the invention described in the claims and the equivalent scope thereof.

100 In-vehicle terminal 110 Control unit 111 Detection information acquisition unit 120 Sensor unit 121 Camera 122 GPS sensor 130 Storage unit 140 Communication unit 150 Output unit 200 Management device 210 Communication device 220 Control device 221 Judgment unit 2211 Image recognition unit 2212 Judgment unit 222 Road information Distribution unit 230 storage device

Claims (8)

A road information distribution system including an in-vehicle terminal that acquires detection information and a management device that can communicate with the in-vehicle terminal and distributes road information based on the detection information.
The in-vehicle terminal is
A first sensor device that captures an image by photographing the front and / or rear of the vehicle on which the in-vehicle terminal is mounted, and
A second sensor device that acquires the first position information indicating the position of the mounted vehicle, and
It is provided with a detection information acquisition unit that acquires the detection information in which the image acquired at a predetermined time and the first position information acquired at the predetermined time are linked.
The management device is
A storage unit that stores the detection information in advance and
Based on the second position information indicating the position of the vehicle to which the road information is distributed, the image associated with the first position information indicating the position within a predetermined range regarding the position of the vehicle to which the road information is distributed. An image recognition unit that executes image recognition processing for
A determination unit for generating the road information regarding the predetermined range based on the determination based on the result of the image recognition process is provided.
The determination unit is a road information distribution system characterized in that the inter-vehicle distance is estimated based on the vehicle included in the image and the road information indicating the degree of congestion of the vehicle is generated. The image recognition unit recognizes the vehicle included in the image and the lane boundary line which is the boundary line between lanes.
The determination unit estimates the inter-vehicle distance based on the vehicle included in the image, and determines the lane in which the mounted vehicle is located among the plurality of lanes based on the position of the lane boundary line included in the image. The road information distribution system according to claim 1, wherein the road information indicating the degree of congestion of the vehicle for each lane is generated based on the inter-vehicle distance and the lane in which the mounted vehicle is located. The detection information further includes information on either the traveling speed of the vehicle or ON / OFF of the brake pedal.
The determination unit is characterized in that it generates the road information indicating the degree of congestion of the vehicle based on the information of either the inter-vehicle distance and the traveling speed or the ON / OFF of the brake pedal. The road information distribution system described in 2. The image recognition unit recognizes the snow cover contained in the image and recognizes the snow cover.
The road information distribution system according to any one of claims 1 to 3, wherein the determination unit generates the road information indicating the snow depth by estimating the snow depth of the snow. The image recognition unit recognizes the road surface included in the image and recognizes the road surface.
The road information distribution system according to any one of claims 1 to 4, wherein the determination unit generates the road information indicating the presence or absence of freezing by determining the presence or absence of freezing on the road surface. The image recognition unit recognizes the pedestrian included in the image and recognizes the face of the pedestrian.
The determination unit estimates the position and number of the pedestrian, estimates the characteristics of the pedestrian based on the face of the pedestrian, and indicates the position and number of the pedestrian and the characteristics of the pedestrian. The road information distribution system according to any one of claims 1 to 5, wherein the road information is generated. A road information distribution device that can communicate with an in-vehicle terminal and distributes road information based on the detection information by collecting detection information from the in-vehicle terminal.
The detection information that links the image of the front and / or rear of the mounted vehicle on which the in-vehicle terminal is mounted at a predetermined time with the first position information indicating the position of the mounted vehicle at the predetermined time is accumulated in advance. Memory part to do
Based on the second position information indicating the position of the vehicle to which the road information is distributed, the image associated with the first position information indicating the position within a predetermined range regarding the position of the vehicle to which the road information is distributed. An image recognition unit that executes image recognition processing for
A determination unit for generating the road information regarding the predetermined range based on the determination based on the result of the image recognition process is provided.
The image recognition unit recognizes the vehicle included in the image and the lane boundary line which is the boundary line between lanes.
The determination unit estimates the inter-vehicle distance based on the vehicle included in the image, and determines the lane in which the mounted vehicle is located among the plurality of lanes based on the position of the lane boundary line included in the image. A road information distribution device, which generates road information indicating the degree of congestion of vehicles in each lane based on the inter-vehicle distance and the lane in which the mounted vehicle is located. Road information based on detection information that links an image of the front and / or rear of the mounted vehicle on which the in-vehicle terminal is mounted at a predetermined time with the first position information indicating the position of the mounted vehicle at the predetermined time. A program that runs on a computer that supports distribution
The first function of accumulating the detection information acquired by the in-vehicle terminal in advance and
Based on the second position information indicating the position of the vehicle to which the road information is distributed, the image associated with the first position information indicating the position within a predetermined range regarding the position of the vehicle to which the road information is distributed. The second function to execute image recognition processing for
Based on the judgment based on the result of the image recognition process, the computer is realized with the third function of generating the road information regarding the predetermined range.
The second function executes the first process of recognizing the vehicle included in the image and the lane boundary line which is the boundary line between lanes.
The third function estimates the inter-vehicle distance based on the vehicle included in the image, and based on the position of the lane boundary line included in the image, determines the lane in which the mounted vehicle is located among a plurality of lanes. A program characterized by executing a second process of determining and generating the road information indicating the degree of congestion of vehicles in each lane based on the inter-vehicle distance and the lane in which the mounted vehicle is located.

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