Patent Description:
A working vehicle that operates while being driven may detect obstacles in the surroundings of the vehicle body by capturing an image of the vehicle body surroundings while being driven and operating using a plurality of cameras and using the captured image of the vehicle body surroundings. Obstacles are detected via an analysis of the captured image by a CPU, ECU, or the like.

Patent Document <NUM>: <CIT>
<CIT> discloses a working vehicle according to the preamble of claim <NUM>, <CIT> discloses a safety system for autonomous operation of off-road and agricultural vehicles using machine learning for detection and identification of obstacles, and<NPL>, relates to techniques to allow a car to be aware of its immediate surroundings in front of it while moving autonomously.

The captured images of the vehicle body surroundings captured using the plurality of cameras corresponds to a very large amount of data. To analyze such a large amount of data of captured images with high accuracy, a processor with high processing power is required. However, there is a limit as to how much processing power a processor installed in a working vehicle can have, making a highly accurate analysis of the captured images of the vehicle body surroundings difficult to perform within a short amount of time.

The present invention is directed at using captured images of vehicle body surroundings to detect obstacles with high accuracy and within a short amount of time.

In order to achieve the object described above, a working vehicle according to an embodiment of the present invention is a working vehicle, as defined in claim <NUM>, capable of operation and driving that includes a plurality of image capture devices that capture an image of surroundings of a vehicle body; a direction detection unit that detects an advancement direction of the operation and driving; an image selection unit that acquires, as a detection image, a surrounding area image captured by one image capture device of the plurality of image capture devices capturing a front advancement direction detected by the direction detection unit; and a detection unit that analyzes the detection image acquired by the image selection unit and detects an obstacle.

Obstacles in the surroundings of the vehicle body can be detected by image analysis of the images captured by the image capture devices. Also, the plurality of cameras may capture images of different sections of the surroundings of the vehicle body, the plurality of surrounding area images may be combined to generate a surroundings image, and the situation of the surroundings of the vehicle body may be displayed via a single image. By using the surroundings image for image analysis in this manner, obstacles in the surroundings of the vehicle body can be detected. However, the analysis device has limits on its performance, and using the surroundings image to detect obstacles with a high accuracy when the amount of data is large is difficult. In regards to this, with the configuration described above, from among the surrounding area images used to generate the surroundings image, the surrounding area image captured by the image capture device capturing the front advancement direction necessary for obstacle detection can be selectively used as the detection image in image analysis. By efficiently optimizing the detection image, obstacle detection can be executed using only the minimum required amount of data for the detection image, the data amount can be reduced, and obstacles can be easily detected with high accuracy in a short time.

Also, an automated driving control unit is provided that executes automated driving control of the operation and driving so that pre-set actions are executed in order.

With such a configuration, even with automated driving, obstacles can be easily detected with high accuracy in a short time.

Also, in a case where an obstacle is detected by the detection unit, the automated driving control unit preferably changes a pre-set next one of the actions.

With such a configuration, situations such as the working vehicle colliding with an obstacle can be avoided, and appropriate operation and driving can be continued.

Also, the image selection unit may selectively acquire, as the detection image, the surrounding area image captured by one image capture device of the plurality of image capture devices capturing a front advancement direction of a next one of the actions a predetermined amount of time before the next one of the actions is started.

With such a configuration, before action transition, obstacles in the advancement direction of the next action can be detected, the action transition being performed regardless of the obstacle can be prevented, and situations such as the working vehicle colliding with an obstacle can be avoided.

Also, the image selection unit selectively acquires, as the detection image, the surrounding area image captured by one image capture device of the plurality of image capture devices capturing a front advancement direction of a next one of the actions a predetermined distance behind a position where the next one of the actions is started.

With such a configuration, before action transition, the presence of obstacles can be identified, the action transition being performed regardless of the obstacle can be prevented, and situations such as the working vehicle colliding with an obstacle can be avoided.

Also, in a case where an obstacle is detected by the detection unit, the automated driving control unit stops transition between the actions, and optionally stops the operation and driving.

With such a configuration, the working vehicle colliding with an obstacle can be reliably avoided. Also, when the obstacle is no longer present, the operation and driving can be restarted or there can be transition between actions. This allows appropriate operation and driving to be continued.

Also, the image selection unit may selectively acquire, as the detection image, the surrounding area image capturing a front advancement direction and the surrounding area image captured by one image capture device of the plurality of image capture devices capturing a region to a side of the vehicle body adjacent to a captured region of the surrounding area image capturing a front advancement direction.

With such a configuration, the data amount of the detection image can be reduced, a detection image with an optimized area can be efficiently selected, and obstacles can be detected with higher accuracy.

Also, the detection unit may detect an obstacle using a neural network trained by machine learning.

With such a configuration, obstacles can be detected more efficiently and with high accuracy.

Also, an image processing unit may be provided that combines the surrounding area images captured by the plurality of image capture devices and generates a surroundings image of an entire surroundings of the vehicle body; and a display device may be provided where the surroundings image is displayed.

With such a configuration, the driver or worker can easily check on the situation of the surroundings of the vehicle body.

Furthermore, an obstacle detection method according to an embodiment of the present invention, as defined in claim <NUM>, is an obstacle detection method for when a working vehicle performs operation and driving that includes capturing images of a surroundings of a vehicle body as a plurality of surrounding area images; detecting an advancement direction of the operation and driving; acquiring, from the plurality of surrounding area images, the surrounding area image capturing a front advancement direction as a detection image; and analyzing the detection image and detecting an obstacle.

Also, an obstacle detection program according to an embodiment of the present invention, as defined in claim <NUM>, is an obstacle detection program for when a working vehicle performs operation and driving that causes a processor to execute processing to acquire a plurality of surrounding area images capturing a surroundings of a vehicle body; processing to detect an advancement direction of the operation and driving; processing to select, from the plurality of surrounding area images, the surrounding area image capturing a front advancement direction as a detection image; and processing to analyze the detection image and detect an obstacle.

Obstacles in the surroundings of the vehicle body can be detected by image analysis of the images captured by the image capture devices. Also, the plurality of cameras may capture images of different sections of the surroundings of the vehicle body, the plurality of surrounding area images may be combined to generate a surroundings image, and the situation of the surroundings of the vehicle body may be displayed via a single image. By using the surroundings image for image analysis in this manner, obstacles in the surroundings of the vehicle body can be detected. However, the analysis device has limits on its performance, and using the surroundings image to detect obstacles with a high accuracy when the amount of data is large is difficult. In regards to this, with the configuration described above, from among the surrounding area images used to generate the surroundings image, the surrounding area image capturing the front advancement direction necessary for obstacle detection can be selectively used as the detection image in image analysis. By efficiently optimizing the detection image, obstacle detection can be executed using only the minimum required amount of data for the detection image, the data amount can be reduced, and obstacles can be easily detected with high accuracy in a short time.

Also, the operation and driving are automated driving controlled so that pre-set actions are executed in order.

Also, in a case where an obstacle is detected, a pre-set next one of the actions is preferably changed.

Also, as the detection image, the surrounding area image capturing a front advancement direction of a next one of the actions may be selectively acquired a predetermined amount of time before the next one of the actions is started.

Also, as the detection image, the surrounding area image capturing a front advancement direction of a next one of the actions is selectively acquired a predetermined distance behind a position where the next one of the actions is started.

Also, when an obstacle is detected, transition between the actions is stopped, and optionally the operation and driving is stopped.

With such a configuration, the working vehicle colliding with an obstacle can be reliably avoided. Also, when the obstacle is no longer present, the operation and driving can be restarted or there can be transition between actions. This allows appropriate operation and driving to be continued.

Also, as the detection image, the surrounding area image capturing a front advancement direction and the surrounding area image capturing a region to a side of the vehicle body adjacent to a captured region of the surrounding area image capturing a front advancement direction may be selectively acquired.

Also, an obstacle may be detected using a neural network trained by machine learning.

Also, the plurality of surrounding area images may be combined and a surroundings image of an entire surroundings of the vehicle body may be generated; and the surroundings image may be displayed.

A standard combine harvester (hereinafter, simply referred to as a combine harvester) is described below with reference to the drawings as an example of a working vehicle according to the present invention. Note that hereinafter, the direction of arrow F in <FIG> is defined as the front, the direction of arrow B is defined as back, the direction to the front of the paper in <FIG> is defined as left, and the direction of the depth of the paper is defined as right. Also, the direction of arrow U in <FIG> is defined as up, and the direction of arrow D is defined as down.

First, the overall configuration of a combine harvester will be described using <FIG>. A combine harvester is provided with a crawler-type propulsion device <NUM>, a driving section <NUM>, a threshing device <NUM>, a grain tank <NUM>, a harvesting unit H, a conveying device <NUM>, a grain discharge device <NUM>, and a satellite positioning module <NUM>. The conveying device <NUM>, the threshing device <NUM>, and the harvesting unit H are examples of work devices.

The propulsion device <NUM> is provided on the lower portion of a vehicle body <NUM>. The combine harvester is configured to be self-propelled via the propulsion device <NUM>.

Also, the driving section <NUM>, the threshing device <NUM>, and the grain tank <NUM> are provided above the propulsion device <NUM>. The driving section <NUM> is provided with a driver seat <NUM> and a cabin <NUM> covering the driver seat <NUM>. The driver seat <NUM> is where the operator of the combine harvester or an observer who monitors the work can sit. Note that the observer may monitor the work of the combine harvester from outside of the combine harvester. A display device <NUM> is disposed in the driving section <NUM>.

The grain discharge device <NUM> is provided above the grain tank <NUM>. Also, the satellite positioning module <NUM> is provided on the upper surface of the driving section <NUM>.

The harvesting unit H is provided on the front portion of the combine harvester. Also, the conveying device <NUM> is provided to the back of the harvesting unit H. Also, the harvesting unit H includes a cutting mechanism <NUM> and a reel <NUM>.

The grain stalk reaped by the cutting mechanism <NUM> is conveyed to the threshing device <NUM> via the conveying device <NUM>. The reaped grain stalk is threshed at the threshing device <NUM>. The grain obtained by threshing is stored in the grain tank <NUM>. The grain stored in the grain tank <NUM> is discharged out of the vehicle by the grain discharge device <NUM> as necessary. The harvesting unit H, the propulsion device <NUM>, the conveying device <NUM>, and the threshing device <NUM> are driven by an engine <NUM>, which is an example of a power source.

The vehicle body <NUM> of the combine harvester is provided with a plurality of cameras <NUM> (corresponding to image capture devices) that capture images of the surroundings of the vehicle body. The plurality of cameras <NUM> each capture an image (surrounding area image) of a predetermined region of the surroundings of the vehicle body <NUM>, and these images are combined to generate an image (surroundings image) of the surroundings in all directions of the vehicle body <NUM>. For example, as the cameras <NUM>, a front camera <NUM> (an example of an image capture device), a back camera <NUM> (an example of an image capture device), a right camera <NUM> (an example of an image capture device), and a left camera <NUM> (an example of an image capture device) are provided. The front camera <NUM>, the back camera <NUM>, the right camera <NUM>, and the left camera <NUM> each capture an image of the surrounding area of the vehicle body <NUM>, generate a surrounding area image, and output the surrounding area image to an image processing unit <NUM> described below (see <FIG>). Note that the surrounding area images in the present embodiment may be still images or may be moving images. Also, the cameras <NUM> are not limited to numbering four, and it is only required that the number of cameras <NUM> is sufficient to capture the entire surroundings of the vehicle body <NUM>.

As illustrated <FIG>, the front camera <NUM> is provided at the front portion of the driving section <NUM>. Specifically, the front camera <NUM> is provided at the front upper portion of the cabin <NUM>. The front camera <NUM> is located at or near the left end portion of the cabin <NUM> in the vehicle body left-and-right direction and located at a central portion of the vehicle body <NUM> in the vehicle body left-and-right direction. The front camera <NUM> is orientated to face diagonally forward and downward and captures images to the front of the vehicle body <NUM>.

The back camera <NUM> is provided at the upper portion of the back end portion of the grain tank <NUM>. The back camera <NUM> is located at or near the left end portion of the grain tank <NUM> in the vehicle body left-and-right direction and located at a central portion of the vehicle body <NUM> in the vehicle body left-and-right direction. The back camera <NUM> is orientated to face diagonally backward and downward and captures images to the back of the vehicle body <NUM>.

The right camera <NUM> is provided at an upper corner portion of the right side portion of the cabin <NUM>. The right camera <NUM> is located at the back end portion of the cabin <NUM> and located at or near the central portion of the vehicle body <NUM> in the vehicle body front-and-back direction. The right camera <NUM> is orientated to face diagonally downward and right and captures images to the right of the vehicle body <NUM>.

The left camera <NUM> is provided at an upper corner portion of the left side portion of the threshing device <NUM>. The left camera <NUM> is located at or near the front end portion of the threshing device <NUM> in the vehicle body front-and-back direction and located at or near the central portion in the vehicle body front-and-back direction. The position of the left camera <NUM> in the vehicle body front-and-back direction is roughly the same as the position of the right camera <NUM> in the vehicle body front-and-back direction. The left camera <NUM> is orientated to face diagonally downward and left and captures images to the left of the vehicle body <NUM>.

The display device <NUM> is provided in the driving section <NUM>. A composite image based on the surrounding area images captured by the front camera <NUM>, the back camera <NUM>, the right camera <NUM>, and the left camera <NUM> is generated, and the composite image is displayed on the display device <NUM>. The display device <NUM> is disposed diagonally left and forward of the driver seat <NUM>.

Next, the configuration of a control system of a combine harvester will be described using <FIG>. The control system of the embodiment includes a control unit <NUM> and is constituted of multiple electronic control units (processors), i.e., ECUs, various operation devices, sensor groups, switch groups, and a wiring network such as an in-vehicle LAN for data transmission between these devices. Note that the control unit <NUM> may be constituted by such hardware, or one or all of the configurations may be constituted by software that execute the appropriate process. Also, such configurations may be implemented via a program executed by a processor. In this case, the program is stored in a discretionary storage device installed in the combine harvester.

The control unit <NUM> is a key element of the control system and is represented as an assembly of ECUs. The control unit <NUM> is connected to the various operation devices, sensor groups, switch groups, and the like via the wiring network. Furthermore, the control unit <NUM> is connected to various devices provided outside of the combine harvester via a communication unit <NUM> in a data communication enabled state.

The communication unit <NUM> is used by the control system of the combine harvester for exchanging data with a cloud computer system <NUM> remotely installed, a mobile communication terminal <NUM>, and the like. The mobile communication terminal <NUM> in this example is a tablet computer operated by an observer (including a driver and worker) at the site of operation and driving.

The positioning data from the satellite positioning module <NUM> and the image data from the cameras <NUM> described above are input to the control unit <NUM> via the wiring network.

The control unit <NUM> is provided with an input processing unit 6A and an output processing unit 6B as an I/O interface. A driving system detection sensor group 8A, an operation system detection sensor group 8B, and the like are connected to the input processing unit 6A. The driving system detection sensor group 8A may include an engine speed adjustment unit, an accelerator pedal, a brake pedal, a transmission operation unit, and other sensors and the like that detect states. The operation system detection sensor group 8B may include sensors and the like that detect the device state of the harvesting unit H, the threshing device <NUM>, the grain discharge device <NUM>, and the conveying device <NUM> and the state of the grain stalk and the grain.

A vehicle driving device group 7A and a work device device group 7B are connected to the output processing unit 6B. The vehicle driving device group 7A may include control devices relating to vehicle driving, such as an engine control device, a transmission control device, a braking control device, a steering control device, and the like. The work device device group 7B may include, for example, a power control device for the harvesting unit H, the threshing device <NUM>, the grain discharge device <NUM>, the conveying device <NUM>.

The control unit <NUM> is provided with an operation and driving control module <NUM>, the image processing unit <NUM>, an obstacle detection unit <NUM>, and a vehicle body position calculation unit <NUM>.

The vehicle body position calculation unit <NUM> calculates the vehicle body position, which corresponds to map coordinates of the vehicle body <NUM>, on the basis of positioning data successively sent from the satellite positioning module <NUM>.

The combine harvester of the embodiment is capable of being driven via both automated driving (automated steering) and manual driving (manual steering). The operation and driving control module <NUM> is provided with an automated driving control unit <NUM> and a travel path setting unit <NUM>, in addition to a driving control unit <NUM> and an operation control unit <NUM>. The driving section <NUM> is provided with a driving mode switch (not illustrated) for selecting either an automated driving mode in which the vehicle is driven with automated steering or a manual steering mode in which the vehicle is driven with manual steering. By operating the driving mode switch, the driving can transition from manual steering driving to automated steering driving or from automated steering driving to manual steering driving.

The driving control unit <NUM> includes an engine control function, a steering control function, a vehicle speed control function, and the like and sends a driving control signal to the vehicle driving device group 7A. The operation control unit <NUM> sends an operation control signal to the work device device group 7B in order to control the movement of the harvesting unit H, the threshing device <NUM>, the grain discharge device <NUM>, the conveying device <NUM>, and the like.

In a case where the manual steering mode is selected, the driving control unit <NUM> generates a control signal on the basis of operation by the driver and controls the vehicle driving device group 7A. Also, on the basis of operation by the driver, the operation control unit <NUM> generates a control signal and controls the work device device group 7B. In a case where the automated steering mode is selected, the driving control unit <NUM> controls the vehicle driving device group 7A relating to steering and the vehicle driving device group 7A relating to vehicle speed on the basis of an automated driving command sent by the automated driving control unit <NUM>. Also, on the basis of an automated driving command sent by the automated driving control unit <NUM>, the operation control unit <NUM> controls the work device device group 7B.

The travel path setting unit <NUM> loads a travel path for the automated driving generated at the control unit <NUM>, the mobile communication terminal <NUM>, the cloud computer system <NUM>, or the like on a memory (not illustrated) built in the travel path setting unit <NUM>. The travel path loaded on the memory (not illustrated) is sequentially used as a target travel path for the automated driving. The travel path can be used in the guidance of the combine harvester to guide it to drive along the travel path even in the case of manual driving. In a case where the automated steering mode is selected, the target travel path and the drive state of the work device device group 7B executed in turn corresponding to the target travel path are set in advance as the action relating to automated driving.

The automated driving control unit <NUM>, more specifically, generates an automated steering command and a vehicle speed command and sends these commands to the driving control unit <NUM>. The automated steering command is generated to eliminate any orientation discrepancy and any position discrepancy between the travel path from the travel path setting unit <NUM> and the vehicle position calculated by the vehicle body position calculation unit <NUM>. The vehicle speed command is generated on the basis of a pre-set vehicle speed value. Furthermore, the automated driving control unit <NUM> sends a work device action command to the operation control unit <NUM> in accordance with the vehicle position and the drive state of the vehicle.

The image processing unit <NUM> acquires the surrounding area images captured by the front camera <NUM>, the back camera <NUM>, the right camera <NUM>, and the left camera <NUM>. Specifically, the image processing unit <NUM> is input with a front surrounding area image of the front area of the vehicle body <NUM> from the front camera <NUM>, input with a back surrounding area image of the back area of the vehicle body <NUM> from the back camera <NUM>, input with a right surrounding area image of the right area of the vehicle body <NUM> from the right camera <NUM>, and input with a left surrounding area image of the left area of the vehicle body <NUM> from the left camera <NUM>. The image processing unit <NUM> generates a surroundings image representing the entire surroundings of the vehicle body <NUM> on the basis of the surrounding area images and outputs the surroundings image to the display device <NUM>. The display device <NUM> displays the surroundings image output by the image processing unit <NUM>.

The image processing unit <NUM> is provided with a storage unit <NUM> and an image combining unit <NUM>.

The storage unit <NUM> stores the vehicle body data indicating the external shape of the vehicle body <NUM>. The vehicle body data may be data indicating the shape of the vehicle body <NUM> in a plan view, may be data indicating the three-dimensional shape of the vehicle body <NUM>, or may be data indicating a 3D model of the vehicle body <NUM>, for example. The vehicle body data includes data indicating the external shape of the harvesting unit H, data indicating the external shape of the grain discharge device <NUM>, and data indicating the external shape of the grain tank <NUM>.

The image combining unit <NUM> generates a surroundings image, which is an image representing the vehicle body <NUM> and the surroundings of the vehicle body <NUM>, on the basis of the four surrounding area images input from the front camera <NUM>, the back camera <NUM>, the right camera <NUM>, and the left camera <NUM> and the vehicle body data stored in the storage unit <NUM> and outputs the surroundings image to the display device <NUM>. The harvesting unit H, the grain discharge device <NUM>, and the grain tank <NUM> are displayed in the surroundings image.

Next, an example of the surroundings image will be described using <FIG> as well as referencing <FIG> and <FIG>. <FIG> is a diagram illustrating an example of a surroundings image <NUM> of a case where the combine harvester is advancing through a field and performing harvesting.

The surroundings image <NUM> is generated by the image combining unit <NUM>. First, the image combining unit <NUM> generates a surroundings composite image <NUM> from the four surrounding area images input from the front camera <NUM>, the back camera <NUM>, the right camera <NUM>, and the left camera <NUM>. The surroundings image <NUM> is generated by the image combining unit <NUM> combining a vehicle body image <NUM> stored in advance in the storage unit <NUM> and the surroundings composite image <NUM>. In the surroundings composite image <NUM> around the vehicle body image <NUM>, a reaped area P to the right and the back of the vehicle body <NUM> and an unreaped area S to the left and the front of the vehicle body <NUM> are displayed.

As illustrated in <FIG>, the obstacle detection unit <NUM> is provided with a direction detection unit <NUM>, an image selection unit <NUM>, and a detection unit <NUM>.

The direction detection unit <NUM> determines the state of the operation and driving acquired from the operation and driving control module <NUM>, a change in the vehicle body position calculated by the vehicle body position calculation unit <NUM>, or determines all of these comprehensively and obtains the advancement direction of the vehicle body <NUM>.

The image selection unit <NUM> determines which one from among the front camera <NUM>, the back camera <NUM>, the right camera <NUM>, the left camera <NUM> (see <FIG> for all) is the camera <NUM> capturing an image of the advancement direction of the vehicle body <NUM> (see <FIG> for this and all following instances) obtained by the direction detection unit <NUM>. The image selection unit <NUM> acquires the surrounding area image captured by the camera <NUM> determined to be the camera <NUM> capturing the advancement direction of the vehicle body <NUM>. For example, in a case where the front is determined to be the advancement direction of the vehicle body <NUM>, the image selection unit <NUM> selectively acquires a front surrounding area image captured by the front camera <NUM> (see <FIG>) as a detection image <NUM> (see <FIG> for this and all following instances). The acquired detection image <NUM> is passed to the detection unit <NUM>.

The detection unit <NUM> analyzes the detection image <NUM> received from the image selection unit <NUM> and detects obstacles. Obstacles can be detected using various image analysis devices or image analysis methods. For example, obstacles can be detected via image analysis using artificial intelligence. Specifically, the detection unit <NUM> may use trained data of a neural network or the like trained via machine learning (deep learning) to detect obstacles. In a case where the detection result corresponds to the presence or absence of obstacles or whether an obstacle can be detected, the detection unit <NUM> transmits the position and type of the obstacle/s to the operation and driving control module <NUM>.

Next, a specific example of obstacle detection will be described using an example of the detection image <NUM> in a case where the vehicle body <NUM> is advancing using <FIG> and referencing <FIG>.

Because in this case the vehicle body <NUM> is advancing, the detection image <NUM> includes an image of the field in front of the harvesting unit H and the vehicle body <NUM>. In a case where there are foreign objects other than crops in the field, the detection unit <NUM> detects foreign objects as obstacles. In the detection image <NUM>, a person F3 is detected as an obstacle.

In this manner, in the present embodiment, when an obstacle is detected, from among the surrounding area images captured by the plurality of cameras <NUM>, the surrounding area image corresponding to the advancement direction of the vehicle body <NUM> is selectively acquired as the detection image <NUM> for analysis. Typically, when the data amount of the image for analysis is large, the analysis capability, including analysis accuracy, analysis speed, and the like, is reduced due to performance constraints of the analysis device or the like. In regards to this, in the present embodiment, the surrounding area image corresponding to the advancement direction of the vehicle body <NUM> is the target for analysis, i.e., the detection image <NUM>, and thus the load on the analysis device or the like is reduced. As a result, the analysis capability, including analysis accuracy, analysis speed, and the like, can be enhanced, and obstacles can be detected with a higher accuracy in a shorter time. Also, the area of the detection image <NUM> is narrowed so that the resolution of the detection image <NUM> can be easily increased. This also allows the detection accuracy of obstacles to be enhanced. Furthermore, by detecting obstacles using only the surrounding area image in the advancement direction of the operation and driving, the detection of obstacles that do not impede the operation and driving can be minimized or prevented, and obstacles with a high likelihood of impeding the operation and driving can be appropriately detected.

Furthermore, when an obstacle is detected, the automated driving control unit <NUM> of the operation and driving control module <NUM> receives an obstacle detection result and changes the action which has been set in accordance with the detection result. When the combine harvester is being automatically driven, the automated driving control unit <NUM> executes control of the operation and driving so that the combine harvester drives along the travel path set by the travel path setting unit <NUM> and the actions for controlling the work device device group 7B are transitioned through in a pre-set order. Also, when an obstacle is detected, the automated driving control unit <NUM> changes the pre-set actions. For example, when a detection result indicating that an obstacle has been detected is received, the automated driving control unit <NUM> stops the vehicle, changes the travel path, stops the work device device group 7B, and changes the state of the work device device group 7B.

As described above, when an obstacle is detected in the advancement direction, the actions relating to automated driving are changed. This helps prevent appropriate operation and driving being impeded by an obstacle. For example, by stopping operation and driving, the obstacle can be removed before operation and driving is once again started. This allows appropriate operation and driving to continue even when there is an obstacle.

Claim 1:
A working vehicle capable of operation and driving, comprising:
a plurality of image capture devices (<NUM>) configured to capture an image of surroundings of a vehicle body (<NUM>); and
a direction detection unit (<NUM>) configured to detect an advancement direction of the operation and driving;
characterized in that the working vehicle further comprises:
an image selection unit (<NUM>) configured to acquire, as a detection image (<NUM>), a surrounding area image captured by one image capture device of the plurality of image capture devices (<NUM>) capturing a front advancement direction detected by the direction detection unit (<NUM>);
a detection unit (<NUM>) configured to analyse the detection image (<NUM>) acquired by the image selection unit (<NUM>) and to detect an obstacle (F1, F2, F3); and
an automated driving control unit (<NUM>) configured to execute automated driving control of the operation and driving so that pre-set actions are executed in order, wherein
the image selection unit (<NUM>) is configured to selectively acquire, as the detection image (<NUM>), the surrounding area image captured by one image capture device of the plurality of image capture devices (<NUM>) capturing a front advancement direction of a next one of the actions a predetermined distance behind a position where the next one of the actions is started, and wherein
in a case where an obstacle is detected by the detection unit (<NUM>) in the image front advancement direction of the next action, the automated driving control unit (<NUM>) is configured to stop transition to the next action until the obstacle is no longer detected.