Apparatus and position estimation method for vehicle

Abstract

An apparatus includes: a vehicle speed acquisition unit configured to acquire a vehicle speed of a vehicle capable of traveling by unmanned driving; a conveying speed acquisition unit configured to acquire a conveying speed of a conveyor on which the vehicle is boarded; and an estimation unit configured to estimate a position of the vehicle using the acquired vehicle speed and the acquired transport speed.

Description

Technical Field

[0001] The present disclosure relates to an apparatus and a method for position estimation of a vehicle. Background Art

[0002] Japanese Unexamined Patent Application Publication (Translation of PCT Application) No. 2017-538619 discloses a technology for causing a vehicle to travel autonomously or by remote control during the manufacturing process of the vehicle. Summary of the invention

[0003] The inventors have found that a vehicle that can travel autonomously or by remote control has the potential to travel not only on a stationary road surface, but also on a moving conveyor. In order for a vehicle to travel properly on a conveyor, a technique is required that enables the position of the vehicle to be properly estimated.

[0004] The present disclosure can be implemented in the following modes.

[0005] According to a first aspect of the present disclosure, the apparatus includes: a vehicle speed acquisition unit configured to acquire a vehicle speed of a vehicle capable of traveling by unmanned driving; a conveying speed acquisition unit configured to acquire a conveying speed of a conveyor on which the vehicle rides; and an estimating unit configured to estimate a position of the vehicle using the acquired vehicle speed and the acquired conveying speed. In this mode, the position of the vehicle is estimated using the vehicle speed of the vehicle and the conveying speed of the conveyor on which the vehicle rides. Accordingly, the position of the vehicle on the conveyor can be appropriately estimated in consideration of the conveying speed of the conveyor. In the device according to the first aspect of the present disclosure, the estimation unit may be configured to estimate the position of the vehicle using the detection result of the external sensor located outside the vehicle, the acquired vehicle speed, and the acquired conveying speed. In this mode, the acquired vehicle speed and conveying speed and the detection result of the external sensor may be used to more appropriately estimate the position of the vehicle on the conveyor. In the device according to the first aspect of the present disclosure, the estimation unit may be configured to estimate the position of the vehicle by correcting the position information about the vehicle based on the acquired vehicle speed and the acquired conveying speed, the position information about the vehicle being acquired using the detection result. In this mode, the position of the vehicle on the conveyor can be estimated more accurately by correcting the position information acquired using the external sensor based on the vehicle speed and the conveying speed. The device according to the first aspect of the present disclosure may further include a command generation unit configured to generate a control command using the estimated position of the vehicle and output the control command, the control command being a control command for causing the vehicle to travel by unmanned driving. In this mode, the control command may be generated using the position of the vehicle estimated in consideration of the conveying speed of the conveyor, and the generated control command may be used to appropriately cause the vehicle to travel on the conveyor. In the apparatus according to the first aspect of the present disclosure, the control command may include a travel control signal for causing the vehicle to travel to a target position on the conveyor. Further, according to the second aspect of the present disclosure, a method for estimating the position of a vehicle includes: obtaining a vehicle speed of a vehicle capable of traveling without human driving; obtaining a conveying speed of a conveyor on which the vehicle rides; and estimating the position of the vehicle using the obtained vehicle speed and the obtained conveying speed.

[0006] In addition to the modes that can be implemented as the above-mentioned apparatus and the above-mentioned method for estimating the position of a vehicle, the present disclosure can also be implemented, for example, as modes such as a system, a program for implementing the method for estimating the position of a vehicle, a non-transitory recording medium having the program recorded therein, and a program product. For example, the program product can be provided as a recording medium having the program recorded therein, or can also be provided as a program product that can be delivered via a network. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will be described below with reference to the accompanying drawings, in which like numerals represent like elements, and in which: Figure 1 is a conceptual diagram showing the configuration of the system in the first embodiment; Figure 2 is a block diagram showing the configuration of the system in the first embodiment; Figure 3 is a flowchart showing a processing flow for driving control of a vehicle in the first embodiment; Figure 4 is a flowchart showing the processing flow of the estimation process; Figure 5 is a block diagram showing the configuration of a system in a second embodiment; and Figure 6 : is a flowchart showing the flow of processing for travel control of a vehicle in the second embodiment. DETAILED DESCRIPTION A. First embodiment:

[0008] Figure 11 is a conceptual diagram showing a configuration of a system 50 in the first embodiment. The system 50 includes one or more vehicles 100 , a server 200 , and one or more external sensors 300 .

[0009] The vehicle 100 may be a vehicle that travels on wheels or a vehicle that travels on tracks, such as a passenger car, a truck, a bus, a two-wheeled vehicle, a four-wheeled vehicle, a tank, an engineering vehicle, etc. In this embodiment, the vehicle 100 is a pure electric vehicle (Battery Electric Vehicle, BEV). The vehicle 100 may be, for example, a gasoline vehicle, a hybrid electric vehicle, or a fuel cell electric vehicle.

[0010] The vehicle 100 is configured to be able to travel by unmanned driving. "Unmanned driving" refers to driving that does not depend on the driving operation of the occupant. The driving operation refers to an operation related to at least one of "moving", "turning" and "stopping" of the vehicle 100. Unmanned driving is achieved by automatic or manual remote control using a device located outside the vehicle 100 or by autonomous control of the vehicle 100. The vehicle 100 that travels by unmanned driving can carry occupants who do not perform driving operations. Examples of occupants who do not perform driving operations include persons who simply sit in a seat of the vehicle 100, and persons who perform work different from driving operations in the vehicle 100, such as equipment, inspection, or switch operations. Driving that depends on the driving operation of the occupant is sometimes referred to as "manned driving".

[0011] In this specification, “remote control” includes “full remote control” in which all actions of the vehicle 100 are completely determined from the outside of the vehicle 100, and “partial remote control” in which some actions of the vehicle 100 are determined from the outside of the vehicle 100. In addition, “autonomous control” includes “full autonomous control” in which the vehicle 100 autonomously controls its own actions without receiving information from a device outside the vehicle 100 at all, and “partial autonomous control” in which the vehicle 100 autonomously controls its own actions by using information received from a device outside the vehicle 100.

[0012] The vehicle 100 only needs to have a configuration that enables the vehicle 100 to move by unmanned driving, for example, it can be in the form of a platform with the configuration described below. Specifically, the vehicle 100 only needs to include at least the vehicle control device and the actuator group described below to realize the three functions of "traveling", "turning" and "stopping" by unmanned driving. In the case of obtaining information from a device outside the vehicle 100 for unmanned driving, the vehicle 100 only needs to further include a communication device. That is, the vehicle 100 that can move by unmanned driving does not need to be provided with a driver's seat and at least some internal components such as an instrument panel, does not need to be provided with at least some external components such as bumpers and fenders, and does not need to be provided with a body shell. In this case, other components (such as a body shell) can be attached to the vehicle 100 before the vehicle 100 is shipped from the factory FC, or other components (such as a body shell) can be attached to the vehicle 100 after the vehicle 100 is shipped from the factory FC without other components (such as a body shell) attached to the vehicle 100. The components may be attached from any directions such as the upper side, the lower side, the front side, the rear side, the right side, and the left side of the vehicle 100 , may be attached in the same direction as each other, or may be attached in different directions from each other.

[0013] In the present embodiment, the system is used in a factory FC that manufactures the vehicle 100. The reference coordinate system of the factory FC is the global coordinate system GC. That is, any position in the factory FC is expressed as an XYZ coordinate under the global coordinate system GC. The factory FC includes a first location PL1 and a second location PL2. The first location PL1 and the second location PL2 are connected by a driving road TR along which the vehicle 100 can travel. In the factory FC, a plurality of external sensors 300 are installed along the driving road TR. The positioning of each external sensor 300 in the factory FC is performed in advance. The vehicle 100 moves from the first location PL1 to the second location PL2 on the driving road TR by unmanned driving. In the present embodiment, the vehicle 100 has the form of a platform during the period during which the vehicle 100 moves from the first location PL1 to the second location PL2. In another embodiment, the vehicle 100 may have the form of a completed vehicle, without being limited to the form of a platform.

[0014] In the present embodiment, the partial driving road TRp as a part of the driving road TR is constituted by a part of the conveyor CV constructed in the factory FC. The conveyor CV is included in the conveyor device CE. The conveyor CV is driven by the conveyor drive unit CD included in the conveyor device CE. For example, the conveyor CV is configured as a belt conveyor including an endless conveyor belt for conveying, a chain conveyor including an endless chain for conveying, and a roller conveyor including a roller for conveying. For example, the conveyor drive unit CD is composed of a motor for generating a driving force and a transmission mechanism such as a gear and a pulley for transmitting the driving force of the motor to the conveyor CV. For example, the conveyor drive unit CD is driven under the control of the server 200 or another computer (not shown) different from the server 200. The conveyor device CE can convey any conveyed object, such as various parts, humans, and various vehicles that are not driven, while moving the vehicle 100 on the conveyor CV. In this case, preferably, the conveyor device CE conveys the conveyed object at a portion different from the partial driving road TRp on the conveyor CV.

[0015] In the present embodiment, the conveying direction TD of the conveyor CV is the same as the target direction Dp of the vehicle 100 on the partial driving road TRp. The target direction Dp refers to the moving direction of the vehicle 100 along the reference route RR described later. That is, the target direction Dp is the direction in which the vehicle 100 moves from the rear side to the front side on the reference route RR. Specifically, each of the conveying direction TD and the target direction Dp in the present embodiment is the +X direction. Various work processes can be performed on the vehicle 100 moving on the conveyor CV. Examples of work processes include processes for attaching components to the vehicle 100 and processes for inspecting parts of the vehicle 100. For example, the work process for the vehicle 100 on the conveyor CV can be performed by a worker or robot riding on the vehicle 100 or the conveyor CV, or it can also be performed by a worker or robot not riding on the conveyor CV. Further, the above-mentioned work process can be performed on the vehicle 100 traveling at a portion of the driving road TR that is not on the conveyor CV, that is, at a portion different from the partial driving road TRp. In this case, for example, the work process may be performed by a worker or a robot riding on the vehicle 100 , or may be performed by a worker or a robot not riding on the vehicle 100 .

[0016] The actual speed of the vehicle 100 moving on the conveyor CV is determined by the vehicle speed of the vehicle 100 and the conveying speed of the conveyor CV. In this specification, "vehicle speed" refers to the relative speed of the vehicle 100 relative to the road surface on which the vehicle 100 is located. The road surface includes not only fixed roads but also moving roads such as conveyor CV. As described later, the vehicle speed can be detected based on a value indicating the rotation speed of the wheel. In addition, in this specification, "actual speed" refers to the absolute speed in the reference coordinate system. That is, the actual speed of the vehicle 100 in this embodiment is the absolute speed of the vehicle 100 under the global coordinate system GC. For example, in the case where the conveying speed of the conveyor CV has a speed component in the same direction as the moving direction of the vehicle 100, depending on the conveying speed of the conveyor CV, the actual speed of the vehicle 100 moving on the conveyor CV is higher than the vehicle speed of the vehicle 100. Specifically, in this case, when the idling and slip of the wheel are not considered, the actual speed of the vehicle 100 is roughly consistent with the speed obtained by adding the vehicle speed to the magnitude of the speed component in the conveying speed having the same direction as the moving direction. On the contrary, in the case where the conveying speed of the conveyor CV has a speed component in the opposite direction to the traveling direction of the vehicle 100, the actual speed of the vehicle 100 moving on the conveyor CV is lower than the vehicle speed of the vehicle 100 depending on the conveying speed of the conveyor CV. Specifically, in this case, when the idling and slipping of the wheels are not considered, the actual speed of the vehicle 100 is substantially consistent with the speed obtained by subtracting the magnitude of the speed component in the conveying speed having the opposite direction to the traveling direction from the vehicle speed. In addition, when the idling and slipping of the wheels are not considered, the actual speed of the vehicle 100 traveling on a fixed road is substantially consistent with the vehicle speed.

[0017] Figure 2 is a block diagram showing the configuration of the system 50. The vehicle 100 includes a vehicle control device 110 for controlling parts of the vehicle 100, an actuator group 120 including one or more actuators driven under the control of the vehicle control device 110, a communication device 130 for communicating with an external device such as a server 200 through wireless communication, and one or more internal sensors 140. The actuator group 120 includes actuators related to the travel of the vehicle 100, such as an actuator of a driving device for accelerating the vehicle 100, an actuator of a steering device for changing the moving direction of the vehicle 100, and an actuator of a braking device for decelerating the vehicle 100. The driving device includes a battery, a driving motor driven by the power of the battery, and a driving wheel rotated by the driving motor. The actuator of the driving device includes a driving motor.

[0018] The internal sensor 140 is a sensor installed in the vehicle 100. Examples of the internal sensor 140 may include a sensor for detecting the motion state of the vehicle 100, a sensor for detecting the operating state of each part of the vehicle 100, and a sensor for detecting the surrounding environment of the vehicle 100. In the present embodiment, the internal sensor 140 includes a vehicle speed sensor for detecting the vehicle speed of the vehicle 100. The vehicle speed sensor detects the vehicle speed based on a value indicating the rotation speed of a wheel included in the vehicle 100 and the diameter of the wheel. As a value indicating the rotation speed of the wheel, for example, the rotation speed of a travel motor included in the vehicle 100 may be used, the rotation speed of an output shaft may be used, or the rotation speed of a wheel acquired by a wheel speed sensor may be used. In addition to the vehicle speed sensor and the wheel speed sensor, examples of the internal sensor 140 may also include a camera, a light detection and ranging (Light Detection And Ranging, LiDAR), a millimeter wave radar, an ultrasonic sensor, a GPS sensor, an acceleration sensor, a gyroscope sensor, and the like.

[0019] The vehicle control device 110 is composed of a computer including a processor 111, a memory 112, an input / output interface 113, and an internal bus 114. The processor 111, the memory 112, and the input / output interface 113 are connected in a bidirectional communication manner via the internal bus 114. The input / output interface 113 is connected to the actuator group 120 and the communication device 130. The processor 111 executes the program PG1 stored in the memory 112, thereby realizing various functions including the function as the vehicle control unit 115.

[0020] The vehicle control unit 115 drives the vehicle 100 by controlling the actuator group 120. The vehicle control unit 115 can drive the vehicle 100 by controlling the actuator group 120 using a driving control signal received from the server 200. The driving control signal is a control signal for driving the vehicle 100. In the present embodiment, the driving control signal includes the acceleration and steering angle of the vehicle 100 as parameters. In another embodiment, instead of or in addition to the acceleration of the vehicle 100, the driving control signal may include the vehicle speed of the vehicle 100 as a parameter.

[0021] The external sensor 300 is a sensor located outside the vehicle 100. The external sensor 300 in the present embodiment is a sensor that captures the vehicle 100 from outside the vehicle 100. Specifically, the external sensor 300 is composed of a camera. The camera as the external sensor 300 acquires a captured image including the vehicle 100, and outputs the captured image as a detection result. The external sensor 300 includes a communication device (not shown), and is capable of communicating with other devices such as the server 200 through wired communication or wireless communication.

[0022] The server 200 is constituted by a computer including a processor 201, a memory 202, an input-output interface 203, and an internal bus 204. The processor 201, the memory 202, and the input-output interface 203 are connected in a bidirectional communication manner through the internal bus 204. The input-output interface 203 is connected to a communication device 205 for communicating with various devices outside the server 200. The communication device 205 can communicate with the vehicle 100 by wireless communication, and can communicate with each external sensor 300 by wired communication or wireless communication. Various information including a program PG2, a reference route RR, a detection model DM, and conveyor position data PD are stored in the memory 202. The processor 201 executes the program PG2 stored in the memory 202, thereby realizing various functions including functions as a remote control unit 210, a determination unit 215, a vehicle speed acquisition unit 220, a conveying speed acquisition unit 230, an estimation unit 240, and a command generation unit 250. The server 200 in the first embodiment corresponds to the "device" in the present disclosure.

[0023] The remote control unit 210 generates a travel control signal for controlling the actuator group 120 of the vehicle 100 using the detection result of the sensor, and causes the vehicle 100 to travel by remote control by sending the travel control signal to the vehicle 100. For example, in addition to generating and outputting the travel control signal, the remote control unit 210 may also generate and output a control signal for controlling an actuator for operating various auxiliary machines and various devices such as wipers, electric windows, and lights included in the vehicle 100. That is, the remote control unit 210 may operate various auxiliary machines and various devices by remote control.

[0024] The determination unit 215 determines whether the vehicle 100 is on the conveyor CV. As described later, in the present embodiment, the determination unit 215 determines whether the vehicle 100 is on the conveyor CV using a captured image acquired by a camera as the external sensor 300. The determination unit 215 may determine that the vehicle 100 is on the conveyor CV when the determination unit 215 detects that all wheels included in the vehicle 100 are on the conveyor CV; or the determination unit 215 may determine that the vehicle 100 is on the conveyor CV when the determination unit 215 detects that some of the wheels included in the vehicle 100 are on the conveyor CV. For example, in the case where the vehicle 100 is a four-wheeled vehicle, the determination unit 215 determines that the vehicle 100 is on the conveyor CV when the determination unit 215 detects that the front wheel in the moving direction of the vehicle 100 is on the conveyor CV, or the determination unit 215 may determine that the vehicle 100 is on the conveyor CV when the determination unit 215 detects that four wheels are on the conveyor CV. The wheels on the front side in the moving direction of the vehicle 100 are the front wheels when the vehicle 100 moves forward, and the rear wheels when the vehicle 100 moves backward. In addition, in another embodiment, the determination unit 215 may determine whether the vehicle 100 is riding on the conveyor CV, for example, using an area sensor that detects that the vehicle 100 has entered an area where the conveyor CV is constructed, or using a sensor that detects an external force or pressure applied to the conveyor CV.

[0025] The vehicle speed acquisition unit 220 acquires the vehicle speed of the vehicle 100. Specifically, the vehicle speed acquisition unit 220 acquires the vehicle speed of the vehicle 100 using a vehicle speed sensor or a wheel speed sensor as the internal sensor 140.

[0026] The conveying speed acquisition unit 230 acquires the conveying speed of the conveyor CV on which the vehicle 100 rides. For example, the conveying speed acquisition unit 230 uses various sensors to detect the movement of the conveyor CV to acquire the conveying speed of the conveyor CV. For example, the conveying speed acquisition unit 230 can use a potentiometer or an encoder provided in the conveyor device CE to acquire the conveying speed of the conveyor CV. The potentiometer or encoder is not limited to a sensor that directly detects the movement of the conveyor CV, and can be composed of, for example, a sensor that detects the rotation speed of the motor or transmission mechanism included in the conveyor drive unit CD. In addition, for example, the conveying speed acquisition unit 230 can use a camera that can capture an image of the conveyor CV to acquire the conveying speed of the conveyor CV. In this case, for example, a mark can be given to the conveyor CV in advance, and the conveying speed acquisition unit 230 can acquire the conveying speed of the conveyor CV based on the change in the position of the mark in the captured image of the camera. In addition, in this embodiment, an external sensor 300 can be used as a camera for acquiring the conveying speed of the conveyor CV.

[0027] In the case where the vehicle 100 is riding on the conveyor CV, the estimation unit 240 estimates the vehicle position of the vehicle 100 using the acquired vehicle speed and conveying speed. The vehicle position is included in the vehicle position information, which is the position information based on which the travel control signal is generated. In the present embodiment, the vehicle position information includes the position and orientation of the vehicle 100 in the global coordinate system GC of the factory FC. Hereinafter, the orientation included in the vehicle position information is also referred to as the vehicle orientation. In the case where the vehicle 100 is not riding on the conveyor CV, the estimation unit 240 in the present embodiment estimates the vehicle position of the vehicle 100 using the vehicle speed.

[0028] The command generation unit 250 generates a control command for driving the vehicle 100 by unmanned driving using the position of the vehicle 100 estimated by the estimation unit 240, and outputs the control command. In the present embodiment, the command generation unit 250 generates a control command using the estimated vehicle position, and transmits the generated control command to the vehicle 100. Further, in the present embodiment, the remote control unit 210 operates as the command generation unit 250. In the present embodiment, the remote control unit 210 operating as the command generation unit 250 generates a driving control signal as a control command.

[0029] Figure 3 1 is a flowchart showing the processing flow for the travel control of the vehicle 100 in the first embodiment. Figure 3 In the processing flow in FIG. 1 , the processor 201 of the server 200 operates as the remote control unit 210, the determination unit 215, the vehicle speed acquisition unit 220, the transport speed acquisition unit 230, the estimation unit 240, and the command generation unit 250 by executing the program PG2. In addition, by executing the program PG1, the processor 111 of the vehicle 100 operates as the vehicle control unit 115.

[0030] In step S1, the processor 201 of the server 200 uses the detection results output from the sensor to obtain vehicle position information about the vehicle 100. In step S1 in the present embodiment, the processor 201 uses the captured image obtained from the camera as the external sensor 300 and the vehicle speed obtained by the internal sensor 140 to obtain the vehicle position information.

[0031] More specifically, in step S1, the processor 201 uses the captured image to obtain the position information of the vehicle 100, and obtains the vehicle position by correcting the position information based on the vehicle speed. Hereinafter, the position information about the vehicle 100 before correction obtained using the external sensor 300 is also referred to as primary position information, and the position information of the vehicle 100 generated by correcting the primary position information at least based on the vehicle speed is also referred to as secondary position information. In addition, the position of the vehicle 100 shown in the primary position information is also referred to as the primary position, and the position of the vehicle 100 shown in the secondary position information is also referred to as the secondary position. In step S1, for example, the processor 201 obtains the primary position information about the vehicle 100 by first detecting the external shape of the vehicle 100 from the captured image, calculating the coordinates of the position measurement point of the vehicle 100 in the coordinate system of the captured image, i.e., the local coordinate system, and converting the calculated coordinates into coordinates in the global coordinate system GC. For example, the external shape of the vehicle 100 included in the captured image can be detected by inputting the captured image into a detection model DM using artificial intelligence. For example, the detection model DM is prepared inside the system 50 or outside the system 50, and is pre-stored in the memory 202 of the server 200. An example of the detection model DM includes a learned machine learning model that has been learned so as to achieve one of semantic segmentation and instance segmentation. As a machine learning model, for example, a convolutional neural network (Convolutional Neural Network, hereinafter referred to as CNN) that has been learned by supervised learning using a learning data set can be used. For example, the learning data set includes a plurality of training images containing the vehicle 100, and labels indicating whether the area in the training image is the area of ​​the vehicle 100 or the area outside the area of ​​the vehicle 100, respectively. When the CNN is learning, the parameters in the CNN are preferably updated by a back-propagation method to reduce the error between the output result of the detection model DM and the label.

[0032] Next, the processor 201 generates secondary position information by acquiring the vehicle speed of the vehicle 100 and correcting the primary position information based on the acquired vehicle speed. Specifically, for example, the processor 201 corrects the primary position information based on the vehicle speed and the time corresponding to the time lag from step S1 to the acquisition of the primary position information to reduce the position deviation between the primary position and the actual position of the vehicle 100 due to the time lag. The time corresponding to the time lag from step S1 to the acquisition of the primary position information includes the time corresponding to the time lag from step S1 to the acquisition of the captured image and the time corresponding to the time lag from the acquisition of the captured image to the acquisition of the primary position information.

[0033] Furthermore, in step S1, for example, the processor 201 may acquire the orientation of the vehicle 100 by estimating the orientation of the vehicle 100 based on the orientation of the moving vector of the vehicle 100 calculated from the position change of the feature point of the vehicle 100 in each frame of the captured image using an optical flow method. For example, the orientation of the vehicle 100 may be acquired using the detection results of a gyro sensor, an acceleration sensor, etc. as the internal sensor 140. Furthermore, the acquired orientation of the vehicle 100 may be used, for example, to perform a correction of the primary position information.

[0034] In step S1 of the present embodiment, specifically, vehicle position information on the vehicle 100 is acquired by executing an estimation process described later.

[0035] In step S2, the processor 201 of the server 200 determines the next target position to which the vehicle 100 will go. In the present embodiment, the target position is represented as XYZ coordinates in the global coordinate system GC. The reference route RR, which is the route along which the vehicle 100 will travel, is pre-stored in the memory 202 of the server 200. The route is shown by a node indicating a departure point, a node indicating a passing point, a node indicating a destination, and links connecting the nodes. The processor 201 determines the next target position to which the vehicle 100 will go by using the vehicle position information and the reference route RR. The processor 201 determines the target position on the reference route RR in front of the current position of the vehicle 100.

[0036] In step S3, the processor 201 of the server 200 generates a driving control signal for driving the vehicle 100 to the determined target position. The processor 201 obtains the vehicle speed from the vehicle 100 and compares the obtained vehicle speed with the target vehicle speed. As a whole, the processor 201 determines the acceleration to accelerate the vehicle 100 when the vehicle speed is lower than the target vehicle speed, and determines the acceleration to decelerate the vehicle 100 when the vehicle speed is higher than the target vehicle speed. In addition, the processor 201 determines the steering angle and the acceleration to prevent the vehicle 100 from deviating from the reference route RR when the vehicle 100 is located on the reference route RR. When the vehicle 100 is not located on the reference route RR, in other words, when the vehicle 100 has deviated from the reference route RR, the processor 201 determines the steering angle and the acceleration to return the vehicle 100 to the reference route RR.

[0037] In step S4, the processor 201 of the server 200 transmits the generated travel control signal to the vehicle 100. The processor 201 repeats the acquisition of vehicle position information, determination of the target position, generation of the travel control signal, and transmission of the travel control signal at a predetermined cycle.

[0038] In step S5, the processor 111 of the vehicle 100 receives the travel control signal transmitted from the server 200. In step S6, the processor 111 of the vehicle 100 controls the actuator group 120 using the received travel control signal, so that the vehicle 100 travels at the acceleration and steering angle shown in the travel control signal. The processor 111 repeats the reception of the travel control signal and the control of the actuator group 120 at a predetermined cycle. With the system 50 in this embodiment, the vehicle 100 can be driven by remote control and the vehicle 100 can be moved without using a transport device such as a crane or a conveyor.

[0039] Figure 4 1 is a flowchart showing the processing flow of the estimation process for realizing the position estimation method for the vehicle 100 in this embodiment. As described above, Figure 4 The estimation process in is performed to obtain Figure 3 The vehicle position information in step S1.

[0040] In step S105, the determination unit 215 determines whether the vehicle 100 is on the conveyor CV. In step S105 in the present embodiment, the determination unit 215 determines whether the vehicle 100 is on the conveyor CV using the position information about the vehicle 100 acquired using the captured image and the conveyor position data PD indicating the construction position of the conveyor CV in the factory FC. For example, the position information about the vehicle 100 used in step S105 is acquired by the same method as the method used to acquire the primary position information. In another embodiment, in step S105, for example, the determination unit 215 may use the primary position information to determine whether the vehicle 100 is on the conveyor CV. In addition, for example, the determination unit 215 may use the corrected primary position information to determine whether the vehicle 100 is on the conveyor CV.

[0041] In the case where it is determined in step S105 that the vehicle 100 is not on the conveyor CV, the processor 201 performs the normal processing in steps S110 to S125. The normal processing is a processing for estimating the vehicle position of the vehicle 100 traveling on a portion of the travel road TR that is not on the conveyor CV, that is, a portion different from the partial travel road TRp. On the other hand, in the case where it is determined in step S105 that the vehicle 100 is on the conveyor CV, the processor 201 performs the conveyor processing in steps S130 to S150. The conveyor processing is a processing for estimating the vehicle position of the vehicle 100 traveling on the conveyor CV of the travel road TR, that is, on the partial travel road TRp.

[0042] In the case where it is determined in step S105 that the vehicle 100 is not on the conveyor CV, the estimation unit 240 acquires a captured image from the camera as the external sensor 300 in step S110. In step S115, the vehicle speed acquisition unit 220 acquires the vehicle speed of the vehicle 100. In step S120, the estimation unit 240 uses the detection model DM and the captured image acquired in step S110 to acquire primary position information about the vehicle 100. Furthermore, in step S120, the estimation unit 240 acquires the orientation of the vehicle 100 using an optical flow method or the like.

[0043] In step S125, the estimation unit 240 estimates the vehicle position using the primary position information obtained in step S120 and the vehicle speed obtained in step S115. Specifically, in step S125, the estimation unit 240 estimates the vehicle position by correcting the primary position information obtained in step S120 based on the vehicle speed obtained in step S115. That is, in step S125, the estimation unit 240 generates secondary position information by correcting the primary position information based on the vehicle speed, and estimates the vehicle position to be the generated secondary position information. As described above, when idling and slipping are not considered, the actual speed of the vehicle 100 traveling on a fixed road surface is roughly consistent with the vehicle speed. Therefore, in step S125, by correcting the primary position information based on the vehicle speed, the vehicle position can be estimated with higher accuracy.

[0044] When it is determined in step S105 that the vehicle 100 is on the conveyor CV, similarly to step S110, in step S130, the estimation unit 240 acquires the captured image. Similar to step S115, in step S135, the vehicle speed acquisition unit 220 acquires the vehicle speed. In step S140, the conveying speed acquisition unit 230 acquires the conveying speed of the conveyor CV. Similar to step S115, in step S145, the estimation unit 240 uses the detection model DM and the captured image acquired in step S130 to acquire the primary position information about the vehicle 100 and acquire the orientation of the vehicle 100.

[0045] In step S150, the estimation unit 240 estimates the vehicle position using the vehicle speed acquired in step S135 and the conveying speed acquired in step S140. In step S150 of the present embodiment, the processor 201 operating as the estimation unit 240 estimates the vehicle position using the captured image, the vehicle speed, and the conveying speed. Specifically, in step S150, the processor 201 operating as the estimation unit 240 estimates the vehicle position by correcting the primary position information acquired using the captured image based on the vehicle speed and the conveying speed. That is, in step S150, the estimation unit 240 generates secondary position information by correcting the primary position information based on the vehicle speed and the conveying speed, and estimates the vehicle position as the generated secondary position information. As described above, the actual speed of the vehicle 100 traveling on the conveyor CV is determined by the vehicle speed and the conveying speed, and therefore, in the case where the vehicle 100 travels on the conveyor CV, the vehicle speed and the conveying speed are reflected in the position deviation between the primary position and the actual position of the vehicle 100. Accordingly, by estimating the vehicle position using the primary position information, the vehicle speed, and the transport speed in step S150 , the vehicle position can be estimated with higher accuracy.

[0046] In step S150, for example, the processor 201 can calculate the actual speed based on the vehicle speed and the conveying speed, and can use the calculated actual speed and the time corresponding to the above-mentioned time lag to correct the primary position information. In this case, for example, the actual speed is calculated by the expression (1) described below. V A =V V +V C ·cosθ……(1) In expression (1), V A Indicates the actual speed, V V represents the magnitude of the vehicle speed, and V C Indicates the magnitude of the conveying speed of the conveyor CV. In addition, θ indicates the angular difference between the conveying direction TD and the moving direction Dt of the vehicle 100. The moving direction Dt indicates the moving direction of the vehicle 100 relative to the road surface of the conveyor CV. As the moving direction Dt, for example, a direction calculated based on the orientation acquired in step S120 or a target direction Dp can be used. In addition, for example, the moving direction Dt can be acquired based on the transition of the vehicle position of the vehicle 100. When the conveying direction TD and the moving direction Dt coincide with each other, the angular difference θ is 0°, and when the conveying direction TD and the moving direction Dt are exactly opposite to each other, the angular difference θ is 180°.

[0047] exist Figure 3In step S3, the processor 201 operating as the command generation unit 250 uses the vehicle position estimated in step S125 or step S150 to output the above control command, ie, the travel control signal.

[0048] In the above-mentioned system 50 in the present embodiment, the vehicle position of the vehicle 100 is estimated based on the vehicle speed of the vehicle 100 and the conveying speed of the conveyor CV on which the vehicle 100 rides. Accordingly, the vehicle position of the vehicle 100 on the conveyor CV can be appropriately estimated in consideration of the conveying speed of the conveyor CV. Furthermore, using the vehicle position appropriately estimated in this way, the travel of the vehicle 100 on the conveyor CV can be appropriately controlled.

[0049] Furthermore, in the present embodiment, the vehicle position of the vehicle 100 is estimated using the captured image and the acquired vehicle speed and conveying speed as the detection result of the external sensor 300. Accordingly, the vehicle position of the vehicle 100 on the conveyor CV can be estimated more appropriately using the acquired vehicle speed and conveying speed and the detection result of the external sensor 300.

[0050] Furthermore, in the present embodiment, the estimation unit 240 estimates the vehicle position of the vehicle 100 by correcting the primary position information about the vehicle 100 acquired using the detection result of the external sensor 300 based on the vehicle speed and the conveying speed. Accordingly, for example, by correcting the primary position information based on the vehicle speed and the conveying speed to reduce the position deviation between the primary position and the actual position of the vehicle 100, the position of the vehicle 100 on the conveyor CV can be estimated more accurately.

[0051] In addition, the present embodiment includes a command generation unit 250 that generates a control command for driving the vehicle 100 by unmanned driving using the vehicle position estimated by the estimation unit 240 and outputs the control command. Accordingly, a control command can be generated based on the vehicle position estimated in consideration of the conveying speed of the conveyor CV, and the generated control command can be used to appropriately drive the vehicle 100 on the conveyor CV. B. Second embodiment:

[0052] Figure 5 2 is a block diagram showing the configuration of the system 50v in the second embodiment. The present embodiment is different from the first embodiment in that the system 50v does not include the server 200. In addition, the vehicle 100v in the present embodiment is capable of traveling by autonomous control of the vehicle 100v. Unless otherwise specified, the other configurations are the same as those in the first embodiment.

[0053] In the present embodiment, the processor 111v of the vehicle control device 110v operates as a vehicle control unit 115v, a determination unit 215, a vehicle speed acquisition unit 220, a conveying speed acquisition unit 230, an estimation unit 240, and a command generation unit 250 by executing a program PG1 stored in a memory 112v. The vehicle control unit 115v acquires the detection result of the sensor, generates a travel control signal using the detection result, and outputs the generated travel control signal to operate the actuator group 120. Thus, the vehicle control unit 115v enables the vehicle 100v to travel by autonomous control. In the present embodiment, the vehicle control unit 115v operates as a command generation unit 250. In the present embodiment, in addition to the program PG1, a detection model DM, a reference route RR, and conveyor position data PD are pre-stored in the memory 112v. The vehicle control device 110v in the second embodiment corresponds to the "device" in the present disclosure.

[0054] Figure 6 1 is a flowchart showing the processing flow for the travel control of the vehicle 100v in the second embodiment. Figure 6 In the processing flow in , the processor 111v of the vehicle 100v operates as the vehicle control unit 115v, the determination unit 215, the vehicle speed acquisition unit 220, the transport speed acquisition unit 230, the estimation unit 240 and the command generation unit 250 by executing the program PG1.

[0055] In step S11, the processor 111v of the vehicle control device 110v uses the detection result output from the camera as the external sensor 300 to obtain the vehicle position information. Figure 3 Similarly to step S1, the processor 111v uses the captured image and the vehicle speed to obtain the vehicle position information. In step S21, the processor 111v determines the next target position to which the vehicle 100v will go. In step S31, the processor 111v generates a travel control signal for causing the vehicle 100v to travel to the determined target position. In step s41, the processor 111v uses the generated travel control signal to control the actuator group 120 so that the vehicle 100v travels according to the parameters shown in the travel control signal. The processor 111v repeats the acquisition of the vehicle position information, the determination of the target position, the generation of the travel control signal, and the control of the actuator group 120 at a predetermined cycle. Using the system 50v in this embodiment, even when the server 200 does not remotely control the vehicle 100v, the vehicle 100v can be driven by the autonomous control of the vehicle 100v.

[0056] In this embodiment, Figure 4The same processing as the position estimation processing in is performed by the processor 111v of the vehicle 100v, for example, at predetermined time intervals. Figure 4 Each step is executed by processor 111v.

[0057] Also in the system 50v in the above-described second embodiment, the vehicle position of the vehicle 100 on the conveyor CV can be appropriately estimated in consideration of the conveying speed of the conveyor CV. C. Other Embodiments

[0058] (C1) In the above embodiment, the external sensor 300 is a camera. However, the external sensor 300 does not need to be a camera, and may be, for example, a LiDAR. In this case, the detection result output by the external sensor 300 may be three-dimensional point cloud data showing the vehicle 100. In this case, the server 200 or the vehicle 100 may obtain the vehicle position information by using the detection point cloud data, i.e., the three-dimensional point cloud data as the detection result, to match the template of the reference point cloud data prepared in advance. In template matching, the matching between the detection point cloud data and the reference point cloud data is started at the starting position. In the case where the matching cannot be completed at the starting position, the matching is performed at the positions around the starting position. In this way, while changing the matching position, the template matching is repeatedly performed until the matching is completed. Preferably, the starting position is, for example, a position close to the vehicle 100 in the measurement point cloud data, so as to avoid a local solution in the template matching or to complete the template matching early.

[0059] Even when the external sensor 300 is a LiDAR and the detection result of the external sensor 300 is three-dimensional point cloud data, in the case where it is determined that the vehicle 100 is riding on the conveyor CV, the estimation unit 240 can estimate the vehicle position of the vehicle 100 using the detection result of the external sensor 300 and the acquired vehicle speed and conveying speed. In this case, the estimation unit 240 can use the acquired vehicle speed and conveying speed to decide the starting position in the template matching. Specifically, for example, the estimation unit 240 can decide the starting position using the vehicle speed, the conveying speed, and the previous position information about the vehicle 100 so that the starting position is a position close to the vehicle 100 in the measurement point cloud data. In this case, as the previous position information about the vehicle 100, for example, the preset travel start position of the vehicle 100, the previously acquired vehicle position information about the vehicle 100, or the completed position in the previous matching can be used. This makes it possible to increase the possibility that the matching between the measurement point cloud data and the reference point cloud data is more appropriately performed, so that the position of the vehicle 100 can be estimated more appropriately through template matching. Furthermore, the estimation unit 240, when determining that the vehicle 100 is on the conveyor CV, can obtain the vehicle position by correcting the position of the vehicle 100 obtained through template matching based on the vehicle speed and the conveying speed, regardless of whether the vehicle speed and the conveying speed are used to determine the starting position in the template matching. That is, the estimation unit 240 can generate secondary position information by correcting the primary position information obtained through template matching based on the vehicle speed and the conveying speed, and can obtain the generated secondary position information as the vehicle position.

[0060] (C2) In the above-described embodiment, in addition to or instead of using the detection result output from the external sensor 300, the estimation unit 240 may also use the detection result output from various internal sensors 140 not limited to the vehicle speed sensor, the wheel speed sensor, the gyro sensor, and the acceleration sensor to acquire the vehicle position information. In this case, for example, the estimation unit 240 may acquire the vehicle position information using the detection result of the camera or LiDAR as the internal sensor 140. Furthermore, the estimation unit 240 may acquire the vehicle position information using the detection result of the internal sensor 140 without using the external sensor 300. In this case, for example, the estimation unit 240 may acquire the vehicle position of the vehicle 100 on the conveyor CV using the position of the vehicle 100 acquired using the detection result of the camera or LiDAR as the internal sensor 140, the vehicle speed, and the conveying speed. Furthermore, for example, the estimation unit 240 may acquire the vehicle position of the vehicle 100 on the conveyor CV using the previous position information on the vehicle 100, the vehicle speed, and the conveying speed. In this case, as the previous position information about the vehicle 100 , for example, a preset travel start position of the vehicle 100 or previously acquired vehicle position information about the vehicle 100 may be used.

[0061] (C3) In the above embodiment, the command generation unit 250 generates a travel control signal as a control command. However, the command generation unit 250 may be configured not to generate a travel control signal as a control command. Specifically, the control command only needs to include at least one of a travel control signal and generation information for generating the travel control signal. For example, in the case where the command generation unit 250 included in the server 200 generates generation information as a control command, the vehicle control device 110 of the vehicle 100 that has received the generation information may use the generation information to generate a travel control signal. As the generation information, for example, vehicle position information, a route, or a target position may be used.

[0062] (C4) In the first embodiment, the processing from the acquisition of the vehicle position information to the generation of the travel control signal is performed by the server 200. However, at least some of the processing from the acquisition of the vehicle position information to the generation of the travel control signal may also be performed by the vehicle 100. For example, the following modes (1) to (3) may be adopted:

[0063] (1) The server 200 may acquire vehicle position information, may determine the next target position to which the vehicle 100 will go, and may generate a route from the current position of the vehicle 100 shown in the acquired vehicle position information to the target position. The server 200 may generate a route to the target position between the current position and the destination, or may generate a route to the destination. The server 200 may send the generated route to the vehicle 100. The vehicle 100 may generate a travel control signal for causing the vehicle 100 to travel on the route received from the server 200, and may control the actuator group 120 using the generated travel control signal.

[0064] (2) The server 200 may acquire the vehicle position information, and may transmit the acquired vehicle position information to the vehicle 100. The vehicle 100 may determine the next target position to which the vehicle 100 will go, may generate a route from the current location of the vehicle 100 shown in the received vehicle position information to the target position, may generate a travel control signal for causing the vehicle 100 to travel on the generated route, and may control the actuator group 120 using the generated travel control signal.

[0065] (3) In modes (1) and (2), for at least one of the generation of the route and the generation of the travel control signal, the detection results output from various internal sensors 140 may be used, without being limited to the detection results output from the vehicle speed sensor, the wheel speed sensor, the gyroscope sensor, and the acceleration sensor. For example, in mode (1), the server 200 may obtain the detection results of the internal sensor 140, and may reflect the detection results of the internal sensor 140 in the route when generating the route. In mode (1), the vehicle 100 may obtain the detection results of the internal sensor 140, and may reflect the detection results of the internal sensor 140 in the travel control signal when generating the travel control signal. In mode (2), the vehicle 100 may obtain the detection results of the internal sensor 140, and may reflect the detection results of the internal sensor 140 in the route when generating the route. In mode (2), the vehicle 100 may obtain the detection results of the internal sensor 140, and may reflect the detection results of the internal sensor 140 in the travel control signal when generating the travel control signal.

[0066] (C5) In the second embodiment, for at least one of the generation of the route and the generation of the travel control signal, the detection results output from various internal sensors 140 may be used, without being limited to the detection results output from the vehicle speed sensor, the wheel speed sensor, the gyro sensor, and the acceleration sensor. For example, the vehicle 100v may acquire the detection results of the internal sensor 140, and may reflect the detection results of the internal sensor 140 in the route when generating the route. The vehicle 100v may acquire the detection results of the internal sensor 140, and may reflect the detection results of the internal sensor 140 in the travel control signal when generating the travel control signal.

[0067] (C6) In the second embodiment, the vehicle 100v uses the detection result of the external sensor 300 to obtain the vehicle position information. However, the vehicle 100v can use the detection result of the internal sensor 140 to obtain the vehicle position information, can determine the next target position to which the vehicle 100v will go, can generate a route from the current location of the vehicle 100v shown in the acquired vehicle position information to the target position, can generate a travel control signal for traveling on the generated route, and can use the generated travel control signal to control the actuator group 120. In this case, the vehicle 100v can travel without using the detection result of the external sensor 300 at all. The vehicle 100v can obtain the target arrival time and congestion information from outside the vehicle 100v, and can reflect the target arrival time and congestion information in at least one of the route and the travel control signal. In addition, the entire functional composition of the system 50v can be provided in the vehicle 100v. That is, the processing implemented by the system 50v in the present disclosure can be implemented only by the vehicle 100v.

[0068] (C7) The vehicle 100 can be manufactured by combining a plurality of modules. A module refers to a unit composed of a plurality of components collected depending on the location or function of the vehicle 100. For example, the platform of the vehicle 100 can be manufactured by combining a front module constituting the front of the platform, a central module constituting the central part of the platform, and a rear module constituting the rear of the platform. The number of modules constituting the platform is not limited to 3, but may be 2 or less or may be 4 or more. In addition, in addition to or instead of the components constituting the platform, the components constituting the parts of the vehicle 100 that are different from the platform can also be modularized. In addition, the various modules may include any external components (such as bumpers and grilles) and any internal components (such as seats and consoles). In addition, not limited to the vehicle 100, any type of movable body can be manufactured by combining a plurality of modules. For example, such a module can be manufactured by joining a plurality of components via welding or fasteners, etc., or can be manufactured by molding at least some of the components constituting the module into one component in one piece by casting. The molding technology for molding a component, especially a relatively large component, in one piece is also referred to as giga casting or mega casting. For example, the front module, the central module, and the rear module may be manufactured by integral casting.

[0069] (C8) The transportation of the vehicle 100 using unmanned driving to drive the vehicle 100 is also referred to as "self-driving transportation". In addition, the configuration for realizing self-driving transportation is also referred to as "vehicle remote control autonomous driving transportation system". In addition, the production method of producing the vehicle 100 using self-driving transportation is also referred to as "self-driving production". For example, in self-driving production, at least a part of the transportation of the vehicle 100 in the factory FC that manufactures the vehicle 100 is realized by self-driving transportation.

[0070] (C9) Some or all of the functions and processes implemented by software in the above-mentioned embodiments may be implemented by hardware. In addition, some or all of the functions and processes implemented by hardware may be implemented by software. As hardware for implementing the various functions in the above-mentioned embodiments, various circuits such as integrated circuits, discrete circuits, etc. may be used, for example.

[0071] The present disclosure is not limited to the above-mentioned embodiments, and can be implemented in various configurations without departing from the spirit of the present disclosure. For example, the technical features in the embodiments corresponding to the technical features in the various modes described in the summary of the invention can be replaced or combined as appropriate to solve some or all of the above-mentioned problems, or to achieve some or all of the above-mentioned effects. In addition, except for the technical features described as necessary in this specification, the technical features can be removed as appropriate.

Claims

1. A device, characterized in that include: a vehicle speed acquisition unit configured to acquire a vehicle speed of a vehicle capable of traveling by unmanned driving; a conveying speed acquisition unit configured to acquire a conveying speed of a conveyor on which the vehicle is riding; as well as An estimating unit is configured to estimate a position of the vehicle using the acquired vehicle speed and the acquired transport speed.

2. The device according to claim 1, characterized in that The estimation unit is configured to estimate the position of the vehicle using a detection result of an external sensor located outside the vehicle, the acquired vehicle speed, and the acquired conveyance speed.

3. The device according to claim 2, characterized in that The estimation unit is configured to estimate the position of the vehicle by correcting position information about the vehicle based on the acquired vehicle speed and the acquired conveyance speed, the position information about the vehicle being acquired using the detection result.

4. The device according to any one of claims 1 to 3, characterized in that A command generation unit is also included, the command generation unit being configured to generate a control command using the estimated position of the vehicle and output the control command, the control command being a control command for causing the vehicle to travel by unmanned driving.

5. The device according to claim 4, characterized in that The control command includes a travel control signal for causing the vehicle to travel to a target position on the conveyor.

6. A method for estimating the position of a vehicle, characterized in that include: Obtaining vehicle speeds of vehicles capable of traveling without human control; Obtaining a conveying speed of a conveyor on which the vehicle is riding; as well as The position of the vehicle is estimated using the acquired vehicle speed and the acquired transport speed.

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