WO2018179345A1 - Trailer - Google Patents

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Publication number
WO2018179345A1
WO2018179345A1 PCT/JP2017/013620 JP2017013620W WO2018179345A1 WO 2018179345 A1 WO2018179345 A1 WO 2018179345A1 JP 2017013620 W JP2017013620 W JP 2017013620W WO 2018179345 A1 WO2018179345 A1 WO 2018179345A1
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WO
WIPO (PCT)
Prior art keywords
vehicle
self
mode
propelled
traveling
Prior art date
Application number
PCT/JP2017/013620
Other languages
French (fr)
Japanese (ja)
Inventor
浩太郎 三木
Original Assignee
本田技研工業株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by 本田技研工業株式会社 filed Critical 本田技研工業株式会社
Priority to PCT/JP2017/013620 priority Critical patent/WO2018179345A1/en
Publication of WO2018179345A1 publication Critical patent/WO2018179345A1/en

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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60PVEHICLES ADAPTED FOR LOAD TRANSPORTATION OR TO TRANSPORT, TO CARRY, OR TO COMPRISE SPECIAL LOADS OR OBJECTS
    • B60P1/00Vehicles predominantly for transporting loads and modified to facilitate loading, consolidating the load, or unloading
    • B60P1/64Vehicles predominantly for transporting loads and modified to facilitate loading, consolidating the load, or unloading the load supporting or containing element being readily removable
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60PVEHICLES ADAPTED FOR LOAD TRANSPORTATION OR TO TRANSPORT, TO CARRY, OR TO COMPRISE SPECIAL LOADS OR OBJECTS
    • B60P9/00Other vehicles predominantly for carrying loads, e.g. load carrying vehicles convertible for an intended purpose
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60RVEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R9/00Supplementary fittings on vehicle exterior for carrying loads, e.g. luggage, sports gear or the like
    • B60R9/06Supplementary fittings on vehicle exterior for carrying loads, e.g. luggage, sports gear or the like at vehicle front or rear
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B62LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62DMOTOR VEHICLES; TRAILERS
    • B62D59/00Trailers with driven ground wheels or the like

Definitions

  • the present invention relates to a following vehicle that travels following a powered motorcycle (self-propelled vehicle).
  • ⁇ Motorcycles have a limited load capacity for passengers other than passengers, especially when two people are riding, the load of luggage is limited to tank bags and side bags.
  • this limited loading capacity for example, use of an unmanned aerial vehicle having a tracking function for tracking a target and capable of loading a load is conceivable (see Patent Document 1).
  • an unmanned aerial vehicle having a tracking function for tracking a target and capable of loading a load is conceivable (see Patent Document 1).
  • the amount of luggage that can be transported can be increased.
  • unmanned airplanes have a limited load capacity and can only be carried lightly. Further, since the power source of power, for example, battery capacity and fuel loading capacity is limited, the flight time is short, and it is difficult to accompany the motorcycle for a long time.
  • the present invention has been made in view of the above-described conventional example, and an object thereof is to provide a follow-up vehicle and a vehicle system that increase the transport capability of the self-propelled vehicle and do not hinder the travel of the self-propelled vehicle.
  • the present invention has the following configuration.
  • a follower vehicle (13) that travels with a self-propelled vehicle (11), Self-propelled means (72) for traveling autonomously by power; Acquisition means (50, 60, 65, 101, 102) for acquiring running state information; A travel control means (112) that travels in any mode of a driven mode that is towed by the self-propelled vehicle and travels autonomously by the self-propelled means (72); The travel control means (112) switches between the driven mode and the self-running mode based on the acquired travel state information.
  • the mode automatically switches depending on the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, the self-propelled mode is set, and even if the driven vehicle is towed, the traveling of the automobile is hindered. Absent. Furthermore, since the following vehicle determines the mode, no restriction is imposed on the towing motorcycle.
  • a vehicle system including a self-propelled vehicle (101) and a follower vehicle (13) that travels with the self-propelled vehicle (101),
  • the following vehicle is Self-propelled means (72) for traveling autonomously by power; Acquisition means (50, 60, 65, 101, 102) for acquiring running state information; Travel control means (112) that travels in one of the following modes: a driven mode that is towed by the self-propelled vehicle; and a self-propelled mode that travels autonomously by the self-propelled means (72); Communication means (65) for receiving an instruction of the mode,
  • the self-propelled vehicle (101) Determination means for switching the operation mode between the driven mode and the self-running mode based on the acquired driving state information; Communication means (11a) for transmitting the driving mode to the following vehicle.
  • the mode automatically switches depending on the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, the self-propelled mode is set, and even if the driven vehicle is towed, the traveling of the automobile is hindered. Absent. Furthermore, since the self-propelled vehicle determines the mode, the configuration of the following vehicle can be simplified.
  • the present invention it is possible to provide a follow-up vehicle and a vehicle system that increase the carrying capacity of a two-wheeled vehicle and do not hinder the traveling of the two-wheeled vehicle.
  • FIG. 1 is an explanatory diagram showing the configuration of the vehicle system.
  • FIG. 2 is an explanatory diagram showing a configuration for controlling the following vehicle.
  • FIG. 3 is an explanatory view showing the arrangement of sensors and control mechanisms of the following vehicle.
  • FIG. 4A is a flowchart showing a switching solution processing procedure of the driving mode of the following vehicle.
  • FIG. 4B is a flowchart showing a traveling control procedure of the following vehicle.
  • FIG. 5 is a flowchart showing the learning process procedure of the driving mode of the following vehicle.
  • FIG. 6A is a flowchart showing variations of operation mode switching parameters.
  • FIG. 6B is a flowchart showing variations of operation mode switching parameters.
  • FIG. 6C is a flowchart showing variations of operation mode switching parameters.
  • FIG. 6D is a flowchart showing variations of operation mode switching parameters.
  • FIG. 7 is a flowchart showing variations of operation mode switching parameters.
  • FIG. 1 shows a configuration of a vehicle system according to the present embodiment.
  • the powered motorcycle 11 is a self-propelled vehicle.
  • the self-propelled vehicle 11 is a two-wheeled vehicle driven by a passenger.
  • the self-propelled vehicle 11 includes a communication unit 11a for communicating with a follow-up vehicle 13 described later, and a traveling state detection unit 11b.
  • the traveling state detection unit 11b detects, for example, the inclination or acceleration of the vehicle as the traveling state.
  • the detected traveling state information is transmitted to the following vehicle by the communication unit 11a.
  • the following vehicle 13 is pulled by the self-propelled vehicle 11 by the towing line 12.
  • the towing line 12 is composed of, for example, a rope or a wire, and has a sufficient tensile strength for towing the following vehicle 13.
  • the following vehicle 13 is coupled to the self-propelled vehicle 11 via the towing line 12.
  • the connection between the self-propelled vehicle 11 and the towing line 12 is removable.
  • the following vehicle 13 includes a travel mechanism unit 13a, a loading unit 13b, a drive wheel 13c, and a steering wheel 13d.
  • the travel mechanism unit 13a includes an engine that is a source of travel drive force, a drive mechanism that drives the drive wheels 13c by the engine, and a control unit 100 that controls travel (described later with reference to FIG. 3). ) Etc. are included.
  • the loading portion 13b is a portion for loading a load, and it is desirable that a mechanism for fixing the load, such as a lid and a fixed rope, is prepared, although not shown in the drawing.
  • Both the driving wheel 13c and the steering wheel 13d rotate freely during towing to reduce the load on the self-propelled vehicle 11.
  • the steering wheel 13d is configured to change its direction according to the towing direction like a caster when towing.
  • an electric motor or a hybrid power unit of the internal combustion engine and the electric motor can be used as the engine.
  • the basic configuration of the vehicle system is as described above, but the towing line 12 may be replaced with a connecting member such as a towing bar having high rigidity such as a metal pipe.
  • a connecting member such as a towing bar having high rigidity such as a metal pipe.
  • a universal joint or the like is provided at both ends or one end of the tow bar so that the direction can be freely changed.
  • the following vehicle has a structure in which a relatively large superstructure is mounted on a small-diameter wheel.
  • a larger-diameter and wider hollow rubber wheel is adopted. May be.
  • the distance between the front and rear of the driving wheel 13c and the steering wheel 13d and the distance between the left and right may be increased for stability during traveling.
  • FIG. 2 shows an example of the inside of the following vehicle 13, in particular, a diagram for explaining the traveling mechanism unit 13 a.
  • FIG. 2 is a view of the following vehicle 13 as viewed from the upper surface or the lower surface.
  • the mechanism unit 13a is provided with a radar 30 and a camera 40 that cover a certain range centering on the front thereof.
  • a road surface sensor 50 is provided toward the road surface.
  • the road surface sensor 50 is configured by, for example, a camera or a radar for detecting the state of a road surface at a certain distance in the traveling direction.
  • the radar 30, the camera 40, and the road surface sensor 50 may be collectively referred to as external sensors.
  • the external sensor is connected to the control unit 100 and an output signal is transmitted to the control unit 100.
  • the controller 100 is connected with a driving force output device 72, a steering device 74, and a brake device 76, and controls these devices.
  • the traveling driving force output device 72 is an engine such as an electric motor or an internal combustion engine, for example, and drives the driving wheel 13 c under the control of the control unit 100 to cause the following vehicle 13 to travel.
  • the driving force output device 72 controls the current if the power is an electric motor, for example, and if it is an internal combustion engine, the fuel injection control based on the intake air amount, the throttle opening, the accelerator opening, and other vehicle information.
  • Main controls such as ignition timing control and electronic throttle valve opening control.
  • the steering device 74 controls the traveling direction of the following vehicle 13 by changing the steering angle (or direction) of the steering wheel 13d under the control of the control unit 100.
  • the steering angle of the steered wheels is determined according to the traveling direction of the self-propelled vehicle 11 traveling in front.
  • the brake device 76 calculates the brake fluid pressure of each wheel based on the brake force, and operates the brake drive unit. Accordingly, the driving wheel 13c and the steering wheel 13d are braked under the control of the control unit 100, and the following vehicle 13 is decelerated or stopped.
  • FIG. 3 shows a configuration example of the operation control system 1.
  • the operation control system 1 is configured by connecting sensors and a control system of a driving device to the control unit 100.
  • the control unit 100 may be configured with a computer, a program executed by the computer, and a memory.
  • a control configuration for automatic operation centering on the control unit 100 will be briefly described.
  • working can also be performed using the technique as described in patent document 2, etc., for example, the following vehicle 13 of this embodiment is limited to such an extent that it can follow the self-propelled vehicle 11 which runs ahead. It suffices if automatic operation is possible.
  • a traveling driving force output device 72, a brake device 76, and a steering device 74 are connected to the control unit 100 as a control system of the driving device.
  • signals related to the external environment are input to the travel control device 112 from sensors including the radar 30, the camera 40, and the road surface sensor 50. Devices for detecting these external environments are sometimes called external detection units.
  • the camera 40 since it is necessary for the following vehicle 13 to recognize the self-propelling vehicle 11 that is the object to be followed, the camera 40 is centered on the front of the following vehicle 13 and the following vehicle 13 is constant from behind the self-propelling vehicle 11. Even if it moves within the range, it is arranged so that the self-propelled vehicle 11 can be photographed.
  • a plurality of cameras 40 may be used to cover the shooting range.
  • the self-propelled vehicle 11 to be followed is recognized by the feature in the image, for example, a sticker or the like depicting a predetermined pattern may be attached to the rear portion of the self-propelled vehicle 11.
  • the posture sensor 60 is a host vehicle state detection unit that detects the posture of the following vehicle such as the direction, acceleration, angular acceleration, and inclination of the following vehicle 13, and an output signal indicating the detected state is input to the control unit 100.
  • the road surface sensor 50 is a detection unit that detects the state of the road surface, and a signal that indicates the state of the road surface that is running is input to the control unit 100.
  • the detected road surface state may be a state related to the friction coefficient of the road surface, for example, the degree of unevenness thereof, or the wetness of the road surface.
  • the GPS receiver 70 receives signals from GPS satellites.
  • the communication unit 65 communicates with the communication unit 11a on the self-propelled vehicle side.
  • the communication unit 65 can receive the traveling state information transmitted from the self-propelled vehicle 11.
  • the control unit 100 mainly controls the driving by using the driving state information and the external environment as input.
  • the own vehicle state recognition unit 101 determines the state of the following vehicle 13 based on, for example, an acceleration input from the attitude sensor 60, each acceleration, direction, or a road surface state signal input from the road surface sensor 50. Identify.
  • the specified state is updated at a predetermined cycle and stored in the storage unit 130 or the like.
  • the specified information includes, for example, a change in speed from the time when braking is started, in addition to information indicating speed, acceleration, traveling direction, road surface condition, and the like at the latest time.
  • a GPS signal is input from the GPS receiver 70 to the vehicle position recognition unit 102.
  • the own vehicle position recognizing unit 102 collates the own vehicle position specified from the GPS signal with the map information 132, for example, and specifies the own vehicle position that can be placed on the map. By identifying the location of the vehicle on the map, you can obtain information registered in association with each location on the map, for example, in addition to the road conditions such as the distance to the next curve entrance and the degree of the curve. Can do. If the road surface state described above is registered in association with the map, the road surface state can also be acquired from the map information.
  • the front-running vehicle recognition unit 103 can recognize an external environment, particularly the self-propelled vehicle 11 traveling immediately before by processing an image of the external environment of the vehicle photographed by the camera 40.
  • the preceding vehicle recognition unit 103 may use the detection result of the radar 30 instead of the camera 40 or together with the camera 40 for recognition of the preceding vehicle.
  • the distance measurement result by the radar 30 can be used for specifying the distance.
  • the forward vehicle recognition unit may include an external detection unit such as the camera 40 or the radar 30.
  • the camera 40 may be configured by integrating the camera body and the image processing unit, or the control unit 100 may perform image processing.
  • the camera 40 is preferably a stereo camera. If a stereo camera is used, the distance to the subject can be estimated based on the parallax of each camera by image processing.
  • the preceding vehicle recognition unit 103 detects the preceding vehicle on the own vehicle traveling path based on the data of the three-dimensional object recognized by the stereo camera, the distance between the own vehicle and the preceding vehicle, the vehicle speed of the preceding vehicle relative to the own vehicle ( Relative speed), acceleration (deceleration) of the preceding vehicle, and the like can also be calculated and output to the travel control unit 12 as preceding vehicle information.
  • the traveling control unit 112 controls traveling of the following vehicle 13 by using information input from part or all of the own vehicle state recognition unit 101, the own vehicle position recognition unit 102, and the preceding traveling vehicle recognition unit 103.
  • the travel is controlled for each operation mode, and the operation mode is determined by the operation mode determination unit 1121 included in the travel control unit 112.
  • traveling state information received from the self-propelled vehicle 11 which is a preceding vehicle is used.
  • the driving mode includes a self-running mode in which driving is autonomously controlled using the power of the own vehicle and a follow-up mode in which the vehicle is towed by a preceding vehicle.
  • the brake is controlled according to the traveling state of the preceding vehicle in order to prevent a rear-end collision.
  • the determined operation mode is stored in the operation mode storage unit 1122.
  • the operation mode storage unit 1122 stores the current operation mode in which the following vehicle 13 is operating and the latest operation mode after the update when the operation mode is updated.
  • the storage unit 130 is a memory or a storage, and includes map information 132 used for driving control, driving state information such as acceleration and / or inclination of a preceding vehicle, and driving state information for determining a driving mode.
  • map information 132 used for driving control
  • driving state information such as acceleration and / or inclination of a preceding vehicle
  • driving state information for determining a driving mode.
  • the switching reference information 133 in which the operation mode determined using as a parameter, the label indicating the evaluation of the quality, and the like are stored is stored.
  • the learning control unit 140 updates and improves the criteria for determining the operation mode with reference to the information accumulated in the switching criterion information 133 or the input label (good / bad information).
  • An example of the processing procedure performed by the learning control unit 140 is shown in FIG. 5, but may be realized by using an artificial intelligence service such as machine learning provided by the cloud. In that case, it is necessary to further have a communication function for connecting to the Internet.
  • the traveling control unit 100 that is the center of the driving control system 1 precedes whether the vehicle travels in the self-running mode in which the follow-up traveling is autonomous or is left to the towing in the follow-up mode that does not use power. Determined according to the traveling state of the self-propelled vehicle In particular, when traveling in the self-propelled mode, based on information from each sensor 30, 40, 50, 60, position information, etc., in order to suppress changes in vehicle body behavior while ensuring tracking accuracy with respect to the preceding vehicle. Then, the cooperative control between the steering control and the deceleration control is optimized and executed.
  • the control unit 100 includes an input device 78 for an operator to input information and the like.
  • the details of the driving force control by the traveling driving force control device 72, the steering angle control by the steering device 74, and the braking control by the brake device 76 are performed, for example, by the configuration and method described in Patent Document 2. I won't go into detail here.
  • FIG. 4A shows an example of an operation mode switching procedure.
  • the procedure of FIG. 4A is executed by the processor. The same applies to the other flowcharts.
  • the traveling control unit 112 acquires traveling state information (S401), and generates an evaluation value from the acquired traveling state information.
  • the generated evaluation value is an index for setting the operation mode to either the self-running mode or the driven mode.
  • the traveling state information that is the basis of the evaluation value is traveling state information that is received from the traveling vehicle 11 and indicates the traveling state of the traveling vehicle 11.
  • the parameters used for generating the evaluation value are stored in the switching reference information 133 in association with the evaluation value.
  • the generated evaluation value is calculated by using an information value as a reference as a parameter, multiplied by a corresponding weight, and added.
  • evaluation value ⁇ (wi ⁇ xi).
  • xi is a parameter
  • wi is its weight.
  • a constant bias value may be added.
  • the reference information includes, for example, acceleration and / or inclination of the vehicle body.
  • the weighting can be improved to a more suitable timing by updating the driving mode switching by machine learning using, for example, accumulated traveling state information as teacher data.
  • the initial value of the weight before learning may be appropriately set, for example, a value learned from data of another vehicle, or all 1 for example.
  • the reference value may be multiplied by the weight instead of the weight multiplied by the parameter, and the weight may be updated by learning.
  • the calculated evaluation value is compared with a predetermined reference value.
  • the reference value is assumed to be the same value as the evaluation value calculated by assuming the running state information near the boundary between the self-running mode and the driven mode and using the value and the weight of each running state information as an initial value. That's fine.
  • the reference value may be one, but may be plural.
  • the reference value for shifting from the free-running mode to the driven mode may be different from the reference value for shifting from the driven mode to the free-running mode. For example, when the evaluation value exceeds the first reference value, the operation mode shifts to one operation mode, and when the evaluation value falls below the second reference value, the operation mode shifts to the other operation mode. It may be a reference value. By doing in this way, the sustainability of the switched operation mode can be improved and frequent switching of the operation mode can be prevented.
  • step S403 the operation mode is determined.
  • the driving mode is set to the self-running mode if the inclination of the vehicle body is large or the negative acceleration is equal to or greater than a certain value.
  • the self-run mode is set when both conditions are satisfied. That is, if the evaluation value exceeds the reference value, the self-running mode is set.
  • the process branches to step S404.
  • the operation mode is the driven mode, and the process branches to step S405.
  • the operation mode determined from the evaluation value is also stored in the switching reference information 133 in association with the parameter that is the basis for calculating the evaluation value.
  • the quality information which shows the driver
  • step S404 the self-running mode is set as the latest driving mode in the driving mode storage unit 1122. Thereafter, the traveling control unit 112 performs traveling control in the self-running mode.
  • step S405 the driven mode is set as the latest operation mode in the operation mode storage unit 1122. Thereafter, the traveling control unit 102 performs traveling control in the driven mode.
  • the self-propelled mode basically, the front-running vehicle recognition unit 103 recognizes the self-propelled vehicle 11 from the image captured by the camera 40, and the travel control unit 112 travels so as to track the recognized self-propelled vehicle 11. Control.
  • step S401 If the operation mode has been set, the process proceeds to step S401 after waiting for a predetermined time.
  • the predetermined time here may be zero. As a result, it is possible to periodically monitor changes in the running state and set an operation mode corresponding to the running state.
  • FIG. 4B shows a travel control procedure by the travel control unit 112 when the operation mode is set.
  • the travel control is also called operation control.
  • the procedure of FIG. 4B is periodically executed asynchronously with FIG. 4A.
  • the latest operation mode stored in the operation mode storage unit 1122 is compared with the current operation mode also stored in the operation mode storage unit 1122 (S411). If they match, it is determined that the operation mode has not changed, and the processing in FIG. 4B ends. If not, the current operation mode is rewritten with the latest operation mode, assuming that the operation mode has been updated (S412). As a result, the current operation mode is updated.
  • the operation mode is changed from the driven mode to the self-running mode, and thus control of each device is started according to the self-running mode (S414). Thereafter, output of the driving force is started (S415). That is, in this example, driving of the electric motor that is power is started.
  • the driving control in the self-running mode is started, and the driving control system 1 controls the following vehicle 13 so as to track the preceding vehicle by controlling driving, braking, and steering in accordance with inputs from various sensors and the like. To do.
  • the self-propelled vehicle 11 that is the preceding vehicle is captured on the image by the camera 40 and / or the radar 30, and the traveling is controlled so as to follow it.
  • the operation is controlled so that no tension other than that due to the weight of the towing line 12 is applied to the towing line 12 so that the operation of the self-propelled vehicle 11 is not restricted.
  • the distance to the preceding vehicle is measured by the radar 30 or the camera 40, and the driving force, the brake, and the steering are controlled so that the distance is within a certain range.
  • the relative speed with respect to the preceding self-propelled vehicle 11 is further measured, and control is performed so as to accelerate when the relative speed becomes negative and decelerate when the relative speed becomes positive.
  • the degree of acceleration and deceleration is a value according to the absolute value of the relative speed.
  • an object to be followed is specified from a captured image of the camera 40, and the steered wheel 13d is controlled at a steering angle corresponding to the speed at that time so as to follow the movement.
  • the traveling control unit 112 continues to control the brake device 76.
  • the brake control for example, the distance from the preceding vehicle is measured by the radar 30 or the camera 40, and the traveling control unit 112 controls the brake device 76 to apply the brake when the distance is equal to or less than a predetermined distance.
  • the relative speed of the following vehicle 13 with respect to the preceding vehicle is measured, and when the relative speed becomes positive, the traveling control unit 112 controls the brake device 76 to apply the brake.
  • the strength of braking may be controlled according to the magnitude of the relative speed.
  • the steering may be controlled in the driven mode. If the follower vehicle 13 is towed by the towing line 12, the follower vehicle 13 has a large degree of freedom of movement and cannot be said to deviate from the lane. Therefore, the steering control may be performed in the same manner as in the self-running mode while the driving force is stopped. In addition, when using a rigid rod instead of the towing line 12, it is not necessary to control the brake.
  • the operation mode is controlled until a new operation mode is set.
  • FIG. 4A the operation mode is switched when the calculated evaluation value satisfies a certain standard.
  • FIG. 5 shows a procedure for learning and improving the weighting for calculating the evaluation value according to the quality of the operation mode switching condition (or switching timing) actually set.
  • the driver of the self-propelled vehicle 11 inputs the switching condition from the input unit, and transmits it to the control unit 100 via the communication unit 65 of the following vehicle 13 by the communication unit 11a.
  • This pass / fail evaluation is used as a label for teacher data.
  • the learning control unit 140 of the control unit 100 executes the procedure of FIG. 5 using the input value.
  • the processor When the learning control unit 140 is realized by executing a program by a processor, the processor becomes an execution subject of the procedure of FIG. Note that this procedure may be performed in real time whenever an input is made, or may be performed in batch by storing the input value in the storage unit 130 in association with the parameter of the evaluation value.
  • the communication unit 65 receives an input value (that is, a label) for pass / fail selection operated by the driver of the self-propelled vehicle 11 (S501).
  • This label is an evaluation of the driver with respect to the last switching of the driving mode, and is used to determine whether or not the driving mode obtained from the parameters accumulated in the teacher data, that is, the switching reference information 133 is correct.
  • the Note that the processing in FIG. 5 may be started by receiving this label as a trigger.
  • the input label is stored in association with the latest switching criterion information that is the basis of the current operation mode (S502).
  • the value of the input label is determined (S503). If the evaluation is “good”, switching to the current operation mode is correct, and in this case, the past operation mode should also be correct, so there is no need to change the evaluation formula. Thus, the process ends.
  • the coefficient, that is, the weight of each parameter in the evaluation value generation formula is recalculated (S504).
  • a bias value that is, a constant
  • the bias value is also included in the weight, and the weight multiplied by each parameter is collectively referred to as a weight vector.
  • the weight vector is changed by, for example, wi ⁇ wi + L ⁇ xi if the weight corresponding to the parameter xi is expressed as wi.
  • L is 1, and ⁇ is a small positive constant.
  • is a value that determines the step of change.
  • may be a different value for each parameter, or the sign may not match.
  • Negative values are used for parameters whose weights are to be reduced by learning, and positive values are used for values that are desired to be increased. In this example, it is a positive value.
  • step S504 if there are a plurality of parameters used for evaluation value calculation, all the weights are recalculated. As a result, the weight is slightly increased and the recalculated evaluation value is increased. Therefore, in this example, the self-running mode is switched with a smaller inclination or a smaller acceleration by changing the weight.
  • the driver is labeled “No” because the switch to self-propelled mode is too slow or the switch to driven mode is too early and feels free driving has been hindered This is because it is considered a case. Since this occurs when the evaluation value is too small with respect to the reference value, in this example, the weight is recalculated in the direction of increasing the evaluation value. This explanation is based on an example where the evaluation value is acceleration or vehicle body tilt, but the same applies when the evaluation value is based on other information.
  • the driver may input whether the switching is too late or too early together with the label. In this case, if the timing is too late (if the evaluation value is too small), the label L may be set to 1, and if it is too early (the evaluation value is too large), L may be set to ⁇ 1 and wi may be recalculated.
  • step S508 it is determined whether the parameter of interest is the last one of the switching reference information 133 (S508). If it is the last, it can be determined that the driving mode can be switched under the conditions required by the driver for all the parameters stored in the switching reference information 133. In that case, the original weight is updated with the recalculated weight (S510).
  • the operation mode switching conditions can be improved by machine learning of the operation mode determination conditions according to the above-described procedure. Thereby, the switching condition of the driving mode desired by the driver can be realized. In addition, if machine learning provided in the cloud or the like is used, higher functions can be used and programs can be easily performed.
  • the driving mode is set to the self-running mode if the inclination or acceleration of the self-propelling vehicle exceeds a predetermined threshold, and the driven mode is set otherwise.
  • Such simple control may be performed. This can be realized by adopting the inclination or acceleration itself of the self-propelled vehicle as the evaluation value and not performing the learning procedure of FIG.
  • the inclination and acceleration which are driving state information, are compared with a reference value, and if the reference value is exceeded, for example, the driving mode is determined to be the self-running mode.
  • step S401 in FIG. 4A acceleration and / or inclination are acquired from the self-propelled vehicle as the driving state information, and an evaluation value is calculated based on the acquired driving state information.
  • an evaluation value is calculated from other parameters.
  • FIG. 6A shows a procedure for determining an operation mode based on the vehicle position acquired from the vehicle position recognition unit 102 as an evaluation value calculation parameter.
  • the distance to the next corner entrance is specified based on the own vehicle position, and the evaluation position is calculated using it as a parameter to determine the operation mode. Specifically, if the distance to the next corner entrance is smaller than the threshold value, the self-running mode is set.
  • the vehicle position specified by the vehicle position recognition unit 102 is acquired.
  • the vehicle position is collated with the map information 132 (S601).
  • an evaluation value is generated using the vehicle position information that can be placed on the map as a parameter (S602).
  • the vehicle position information specified here includes, for example, a distance to the next corner entrance.
  • the distance from the immediately preceding corner exit may be included. For example, if the position of the corner entrance or exit is stored in the map information, the following vehicle 13 determines the distance from the position of the own vehicle and the traveling direction to the entrance of the next curve on the map and / or the distance from the exit. Can be identified. The distance is used as a parameter for calculating the evaluation value.
  • the operation mode can be switched based on the vehicle position, particularly the distance to the next corner entrance.
  • the mode can be switched to the automatic mode, and the restriction of driving can be reduced or eliminated by the following vehicle during corner traveling it can.
  • the energy consumption of the following vehicle can be suppressed by switching to the driven mode after passing the corner.
  • the machine learning via the evaluation value described in this example is not performed, and the operation mode is controlled to the self-running mode if the distance to the next corner is smaller than the predetermined threshold, and the driven mode is set otherwise. May be. Therefore, the procedure of FIG. 5 is not executed, and the distance to the next corner may be used as the evaluation value.
  • FIG. 6B shows a procedure for determining the operation mode based on the start of braking, that is, the speed change from the braking point, as an evaluation value calculation parameter.
  • the self-running mode is set when the speed change from the start of braking exceeds a threshold value.
  • a threshold value For this purpose, first, for example, a signal indicating that the vehicle has been braked is received from the self-propelled vehicle 11. Then, the speed change is specified based on this time (S611). An evaluation value is generated from the identified speed change in the same manner as in step S602. Further, without receiving a signal from the self-propelled vehicle 11, for example, the lighting of a brake lamp in an image acquired by the camera 40 may be recognized, and the time point may be specified as a braking point.
  • machine learning via the evaluation value is not performed, and the operation mode may be controlled to the self-running mode if the speed change exceeds a predetermined threshold value, and to the driven mode otherwise. . Therefore, the procedure of FIG. 5 is not executed, and the speed change itself from braking is used as the evaluation value.
  • the operation mode can be switched based on the speed change after the braking is started. Since braking is often applied when entering a corner, this control allows the following vehicle to be set to the self-propelled mode when passing the corner.
  • FIG. 6C shows a procedure for determining the operation mode based on the start of braking, that is, the elapsed time from the braking point, as an evaluation value calculation parameter.
  • the self-running mode is set. For this purpose, first, for example, a signal indicating that the vehicle has been braked is received from the self-propelled vehicle 11. Then, the elapsed time is specified based on this time point (S621). An evaluation value is generated from the specified elapsed time in the same manner as in step S602. However, the evaluation value is generated every predetermined time. Further, without receiving a signal from the self-propelled vehicle 11, for example, the lighting of a brake lamp in an image acquired by the camera 40 may be recognized, and the time point may be specified as a braking point.
  • the machine learning via the evaluation value is not performed, and the operation mode may be controlled to the self-running mode if the elapsed time exceeds a predetermined threshold, and the driven mode may be controlled otherwise. . Therefore, the procedure shown in FIG. 5 is not executed, and the elapsed time from braking itself may be used as the evaluation value.
  • the operation mode can be switched based on the elapsed time from the start of braking. Since braking is often applied when entering a corner, this control allows the following vehicle to be set to the self-propelled mode when passing the corner.
  • FIG. 6D shows a procedure when using road surface state information acquired from the vehicle state recognition unit 101 or the road surface sensor 50 as an evaluation value calculation parameter. Specifically, for example, if the friction coefficient exceeds a threshold value as the evaluation value of the road surface state, the self-running mode is set. For this purpose, first, the road surface state detected by the vehicle state recognition unit 101 or the road surface sensor 50 is acquired (S631). Next, an evaluation value is generated from the road surface state information (S632).
  • the road surface state information may include a road surface inclination, a friction coefficient, and the like.
  • the inclination of the road surface may be obtained by acquiring inclination information of the own vehicle from the attitude sensor 60 or the own vehicle state recognition unit 101 and regarding the inclination as the inclination of the road surface.
  • wetting or unevenness may be detected from the road surface image taken by the road surface sensor 50, and the approximate friction coefficient may be estimated based on the detected wetness or unevenness.
  • the road surface image pattern having a known friction coefficient is compared with the road surface image captured by the road surface sensor 60, and the friction coefficient previously associated with the matching or similar pattern is determined as the friction coefficient of the current road surface. It may be used as Since the parameter to be used is changed, the weight may be a value different from that in step S401.
  • the operation mode can be switched based on the road surface condition.
  • the self-propelled mode and the driven mode based on the road surface state, for example, on an uphill road, it is possible to reduce the burden on the self-propelled vehicle 11 that switches to the automatic mode. Further, on a slippery road surface, it becomes more slippery by applying a driving force to the wheels. Therefore, it is possible to make the following vehicle less likely to slip by switching to the driven mode.
  • machine learning via the evaluation value is not performed, and control is performed so that the driving mode is set to the self-running mode if the road slope or the friction coefficient exceeds a predetermined threshold, and the driven mode is set otherwise. May be.
  • the procedure shown in FIG. 5 is not executed, and a value representing the road surface condition may be used as the evaluation value.
  • the parameter serving as a reference for the evaluation value is not limited to the parameter described above, and other values may be used.
  • the traveling state of the following vehicle 13 measured by the following vehicle the traveling state of the traveling vehicle measured by the traveling vehicle 11 and transmitted to the following vehicle 13, acquired by a sensor, etc.
  • driver's physiological information such as heart rate and blood pressure, presence / absence of passengers, model number of self-propelled vehicle, type of tires, etc.
  • the evaluation value may be calculated from all or part of the information, and the operation mode may be switched.
  • the evaluation value may be obtained by the sum of values obtained by multiplying each of the adopted parameters by weight, or an intermediate evaluation value is calculated from the parameters described as each variation, and the intermediate evaluation value is calculated.
  • a multilayer structure in which a final evaluation value is calculated by weighting may be adopted.
  • FIG. 7 shows a procedure when the driving state information and the driver information are used as the evaluation value calculation parameters.
  • traveling state information including the inclination of the self-propelled vehicle and the posture of the driver (rider) is acquired from the image acquired by the camera 40 (S701).
  • the driver's posture and the inclination of the vehicle body are detected, for example, by identifying the axis from the contour identified from the image and tilting the axis.
  • the inclination is recognized by recognizing the object of the preceding vehicle from the image taken by the camera 40 and specifying the upper and lower axes from the contour. Can be identified.
  • the following vehicle 13 is a four-wheeled vehicle. If it is assumed that the following vehicle 13 is not inclined, the inclination with respect to the image frame can be directly specified as the inclination of the self-propelled vehicle. Further, the driver's posture can be specified in the same manner.
  • the received information includes, for example, engine output, selected gear, degree of braking, acceleration, each acceleration, and the like. Therefore, in this embodiment, the self-propelled vehicle is provided with a sensor that detects such information. Since the engine output itself may be difficult to measure, it may be replaced with the engine speed. The degree of braking may be replaced with information indicating the position of the break lever or pedal, for example.
  • an evaluation value is generated using the acquired information as a parameter (S703).
  • the sum obtained by weighting all acquired parameters may be used as the evaluation value, but the evaluation value calculated from the information related to the driver and the evaluation value calculated from the information related to the traveling state of the self-propelled vehicle are calculated.
  • an operation weighted to each of the evaluation values may be calculated as a final evaluation value.
  • This evaluation value calculation process constitutes a vehicle-rider model that is comprehensively obtained from the driver's state and the traveling state of the self-propelled vehicle.
  • the weights of all the parameters may not be uniformly increased, and a parameter for increasing the weight may be selected at random.
  • various combinations of parameter values and labels for the parameter values may be prepared in advance and learned as teacher data using, for example, a machine learning service provided as a cloud service. By doing so, the operation mode can be switched with higher accuracy.
  • the third embodiment relates to a method for supplying energy to the following vehicle 13.
  • the following vehicle itself holds an energy source such as a battery and fuel.
  • cordless power feeding is performed from the self-propelled vehicle to the following vehicle, and the following vehicle 13 is driven.
  • the distance between the self-propelled vehicle and the following vehicle is considered to be about several meters, for example, power transmission by a magnetic field resonance method or a microwave method is adopted. Since the magnetic field resonance method has a higher efficiency as the distance between the resonators is shorter, the resonators to be mounted on the self-propelled vehicle and the following vehicle, for example, are not arranged in front and back, but are arranged so as to overlap each other. You may comprise so that the distance between resonators may not change greatly even if the distance of a vehicle and a following vehicle changes. By configuring in this way, collision between resonators can also be prevented.
  • the present embodiment it is not necessary to load batteries and fuel that lead to an increase in the weight of the following vehicle, and the weight can be reduced.
  • the following vehicle can be self-propelled as long as it can receive power from the self-propelled vehicle.
  • the structure of the loading part of the tracking vehicle 13 can be varied according to the objective.
  • various configurations are used according to purposes such as cargo, accommodation, and pet transportation.
  • only the loading unit shown in FIG. 1 can be replaced, and one following vehicle can be used for multiple purposes.
  • This configuration increases the user's choice and allows the vehicle to be used for various purposes.
  • the first aspect is as follows.
  • the mode is automatically switched according to the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, it becomes the self-propelled mode and does not impair the touring comfort even if the driven vehicle is towed. .
  • the second aspect is as follows.
  • the following vehicle A communication means (65); The follow-up vehicle, wherein the acquisition means (103) acquires the traveling state information of the self-propelled vehicle as the traveling state information from the self-propelled vehicle via the communication means (65).
  • the following vehicle need not have a configuration for detecting the traveling state of the self-propelled vehicle, and the configuration can be simplified.
  • the third aspect is as follows.
  • the following vehicle includes a road surface state detection unit (50) for detecting a road surface state, and acquires the road surface state as the traveling state information.
  • a road surface state detection unit (50) for detecting a road surface state, and acquires the road surface state as the traveling state information.
  • the mode is automatically switched depending on the road surface condition, so that it is possible to travel as if driving a self-propelled vehicle alone without paying attention to the driven vehicle being towed.
  • the fourth aspect is as follows.
  • Position detecting means (102) for detecting position information for detecting position information
  • the follow-up vehicle wherein the acquisition unit acquires a position on a map indicated by the map information as the traveling state.
  • the fifth aspect is as follows.
  • the self-propelled vehicle is a motorcycle (11), Photographing means (40) for photographing the two-wheeled vehicle and a rider riding on the two-wheeled vehicle to obtain image data; Means (112, S702) for obtaining posture information indicating the inclination of the self-propelled vehicle and the posture of the rider based on the image data photographed by the photographing means (40);
  • the follow-up vehicle wherein the acquisition means acquires the posture information as the traveling state information.
  • This configuration allows the driving mode to be controlled without acquiring information from the self-propelled vehicle, thereby simplifying the configuration of the self-propelled vehicle.
  • the sixth aspect is as follows.
  • the travel control means (112) further receives an instruction from the self-propelled vehicle by the communication means (65), and switches between the driven mode and the self-propelled mode based on the instruction.
  • This configuration eliminates the need for control for switching the operation mode, thereby further simplifying the configuration.
  • the seventh aspect is as follows.
  • Storage means (133) for storing the running state information when the driven mode and the self-running mode are switched by the running control means, and the driving mode corresponding to the running state information;
  • Input means (11a) for inputting the pass / fail of switching of the operation mode as a pass / fail signal, and further storing the storage state information and the operation mode in association with the storage means;
  • a follow-up vehicle further comprising learning means (140) for correcting timing for switching between the driven mode and the self-running mode based on the pass / fail signal and the corresponding running state information.
  • This configuration enables the operation mode to be switched at the timing desired by the driver with the learning function.
  • the eighth aspect is as follows.
  • This configuration allows the following vehicle to track a self-propelled vehicle.
  • the ninth aspect is as follows.
  • a vehicle system including a self-propelled vehicle (101) and a following vehicle (103) that travels with the self-propelled vehicle (101),
  • the following vehicle is Self-propelled means (72) for traveling autonomously by power; Acquisition means (50, 60, 65, 101, 102) for acquiring running state information; Travel control means (112) that travels in one of the following modes: a driven mode that is towed by the self-propelled vehicle; and a self-propelled mode that travels autonomously by the self-propelled means (72); Communication means (65) for receiving an instruction of the mode,
  • the self-propelled vehicle (101) Determination means for switching the operation mode between the driven mode and the self-running mode based on the acquired driving state information;
  • the vehicle system which has a communication means (11a) which transmits the said driving mode to the said following vehicle.
  • the mode is automatically switched according to the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, it becomes the self-propelled mode and does not impair the touring comfort even if the driven vehicle is towed. . Furthermore, since the self-propelled vehicle determines the mode, the configuration of the following vehicle can be simplified.
  • the tenth aspect is as follows.
  • the following vehicle includes a weight, an engine output, a speed, an acceleration of the following vehicle, a slope when the automobile is a two-wheeled vehicle, and a distance to a corner entrance in the traveling state.
  • This configuration makes it possible to determine the operation mode with various parameters and to perform fine control.
  • the eleventh aspect is as follows.
  • the traveling control means detects braking of the self-propelled vehicle regardless of whether it is in the self-propelled mode or the driven mode, and applies braking when detecting the braking of the self-propelled vehicle. .
  • This configuration can prevent a rear-end collision with a self-propelled vehicle.
  • the twelfth aspect is as follows.
  • the following vehicle Autonomous traveling by the self-propelled means is performed using electric power as an energy source,
  • the following vehicle further includes cordless power receiving means that receives cordless power supply from the self-propelled vehicle.
  • This configuration makes it possible to reduce the weight of the following vehicle and to increase the distance traveled in the self-running mode.
  • the thirteenth aspect is as follows.
  • a follow-up vehicle further comprising an exchangeable loading means for loading a load.
  • This configuration makes it possible to use the loading means desired by the user.
  • 1 driving control system 11 self-propelled vehicle, 12 towing, 13 following vehicle, 100 control unit, 112 driving control unit, 1121 driving mode determining unit, 1122 driving mode, 140 learning control unit

Abstract

This trailer (13) is towed with a towing means (12) by an automotive vehicle (11). The trailer (13) travels in one of two driving modes: moving autonomously in an autonomous mode or being towed in trailer mode. For example, the trailer will, on the basis of drive condition data such as acceleration and tilt reported by the automotive vehicle (11), set the driving mode to the autonomous mode if the data indicates acceleration or tilt conditions that exceeds a fixed value, and to trailing mode if not. In the automatic mode, the trailer (13) follows the automotive vehicle (11) and reduces the burden thereon.

Description

追従車両Following vehicle
 本発明は、動力付きの二輪車(自走車)に追従して走行する追従車両に関する。 The present invention relates to a following vehicle that travels following a powered motorcycle (self-propelled vehicle).
 自動二輪車は乗員以外の荷物の積載量が限られており、特に二人乗車時には、荷物の積載はタンクバッグやサイドバッグなどに限られる。この限られた積載能力を拡大するために、たとえば目標を追跡する追跡機能を有し、荷物の積載が可能な無人航空機の利用などが考えられる(特許文献1参照)。この無人航空機に荷物を積み、走行する二輪車を目標として追跡させることで、運搬できる荷物の量を増やすことができる。 ¡Motorcycles have a limited load capacity for passengers other than passengers, especially when two people are riding, the load of luggage is limited to tank bags and side bags. In order to expand this limited loading capacity, for example, use of an unmanned aerial vehicle having a tracking function for tracking a target and capable of loading a load is conceivable (see Patent Document 1). By loading luggage on this unmanned aerial vehicle and tracking a traveling two-wheeled vehicle as a target, the amount of luggage that can be transported can be increased.
特開2017-503226号公報JP 2017-503226 A 特開2017-19308号公報JP 2017-19308 A
 しかしながら、無人飛行機は荷物の積載量が限定的であり、運搬できる荷物は軽量なものに限られる。また、動力のエネルギー源、たとえば電池容量や燃料の積載容量も限られているため飛行時間が短く、二輪車の長時間の走行に伴走することは困難である。 However, unmanned airplanes have a limited load capacity and can only be carried lightly. Further, since the power source of power, for example, battery capacity and fuel loading capacity is limited, the flight time is short, and it is difficult to accompany the motorcycle for a long time.
 また、自転車に用いられるような車両型の搬送装置を自走車(二輪車)によりけん引することで荷物の搬送能力を拡大することも考えられる。しかしながら自動二輪車の走行速度は自転車に比べて速く、道路のカーブなどでは、牽引された搬送装置が車線を逸脱したり、また、けん引する二輪車の走行を妨げたりすることもあり得る。 Also, it is conceivable to expand the load carrying capacity by towing a vehicle-type carrying device used for bicycles by a self-propelled vehicle (two-wheeled vehicle). However, the traveling speed of a motorcycle is faster than that of a bicycle, and on a road curve or the like, the towed conveyance device may deviate from the lane, or the traveling of the towing motorcycle may be hindered.
 本発明は上記従来例に鑑みて成されたもので、自走車の運搬能力を拡大するとともに、自走車の走行を妨げることのない追従車両および車両システムを提供することを目的とする。 The present invention has been made in view of the above-described conventional example, and an object thereof is to provide a follow-up vehicle and a vehicle system that increase the transport capability of the self-propelled vehicle and do not hinder the travel of the self-propelled vehicle.
 上記目的を達成するために本発明は以下の構成を有する。 In order to achieve the above object, the present invention has the following configuration.
 すなわち、本発明の一側面によれば、自走車(11)と共に走行する追従車両(13)であって、
 動力により自律的に走行するための自走手段(72)と、
 走行状態情報を取得する取得手段(50,60,65,101,102)と、
 前記自走車にけん引されて走行する従動モードと、前記自走手段(72)により自律的に走行する自走モードの何れかのモードで走行する走行制御手段(112)と、を有し、
 前記走行制御手段(112)は、取得した前記走行状態情報に基づいて、前記従動モードと前記自走モードとを切り替える。
That is, according to one aspect of the present invention, a follower vehicle (13) that travels with a self-propelled vehicle (11),
Self-propelled means (72) for traveling autonomously by power;
Acquisition means (50, 60, 65, 101, 102) for acquiring running state information;
A travel control means (112) that travels in any mode of a driven mode that is towed by the self-propelled vehicle and travels autonomously by the self-propelled means (72);
The travel control means (112) switches between the driven mode and the self-running mode based on the acquired travel state information.
 この構成により、自走車の走行状態によって自動的にモードが切り替わることで、自走車を自在に操作したいときには、自走モードとなり、従動車を牽引していても自動車の走行を妨げることがない。さらに、モードの決定を追従車両が行うことで、けん引する二輪車に制限が課されない。 With this configuration, the mode automatically switches depending on the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, the self-propelled mode is set, and even if the driven vehicle is towed, the traveling of the automobile is hindered. Absent. Furthermore, since the following vehicle determines the mode, no restriction is imposed on the towing motorcycle.
 あるいは本発明の他の一側面によれば、自走車(101)と、自走車(101)と共に走行する追従車両(13)とを含む車両システムであって、
 前記追従車両は、
 動力により自律的に走行するための自走手段(72)と、
 走行状態情報を取得する取得手段(50,60,65,101,102)と、
 前記自走車にけん引されて走行する従動モードと、前記自走手段(72)により自律的に走行する自走モードの何れかの運転モードで走行する走行制御手段(112)と、
 前記モードの指示を受信する通信手段(65)とを有し、
 前記自走車(101)は、
 取得した前記走行状態情報に基づいて、運転モードを、前記従動モードと前記自走モードとで切り替える決定手段と、
 前記運転モードを前記追従車両に送信する通信手段(11a)と
を有する。
Alternatively, according to another aspect of the present invention, there is provided a vehicle system including a self-propelled vehicle (101) and a follower vehicle (13) that travels with the self-propelled vehicle (101),
The following vehicle is
Self-propelled means (72) for traveling autonomously by power;
Acquisition means (50, 60, 65, 101, 102) for acquiring running state information;
Travel control means (112) that travels in one of the following modes: a driven mode that is towed by the self-propelled vehicle; and a self-propelled mode that travels autonomously by the self-propelled means (72);
Communication means (65) for receiving an instruction of the mode,
The self-propelled vehicle (101)
Determination means for switching the operation mode between the driven mode and the self-running mode based on the acquired driving state information;
Communication means (11a) for transmitting the driving mode to the following vehicle.
 この構成により、自走車の走行状態によって自動的にモードが切り替わることで、自走車を自在に操作したいときには、自走モードとなり、従動車を牽引していても自動車の走行を妨げることがない。さらに、モードの決定を自走車が行うことで、追従車両の構成を簡単化できる。 With this configuration, the mode automatically switches depending on the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, the self-propelled mode is set, and even if the driven vehicle is towed, the traveling of the automobile is hindered. Absent. Furthermore, since the self-propelled vehicle determines the mode, the configuration of the following vehicle can be simplified.
 本発明によれば、二輪車の運搬能力を拡大するとともに、二輪車の走行を妨げることのない追従車両および車両システムを提供できる。 According to the present invention, it is possible to provide a follow-up vehicle and a vehicle system that increase the carrying capacity of a two-wheeled vehicle and do not hinder the traveling of the two-wheeled vehicle.
 本発明のその他の特徴及び利点は、添付図面を参照とした以下の説明により明らかになるであろう。なお、添付図面においては、同じ若しくは同様の構成には、同じ参照番号を付す。 Other features and advantages of the present invention will become apparent from the following description with reference to the accompanying drawings. In the accompanying drawings, the same or similar components are denoted by the same reference numerals.
 添付図面は明細書に含まれ、その一部を構成し、本発明の実施の形態を示し、その記述と共に本発明の原理を説明するために用いられる。
図1は車両システムの構成を示した説明図である。(第一実施例) 図2は、追従車両の制御のための構成を示した説明図である。(第一実施例) 図3は追従車両のセンサおよび制御機構の配置を示した説明図である。(第一実施例) 図4Aは追従車両の運転モードの切り替え解処理手順を示したフロー図である。(第一実施例) 図4Bは追従車両の走行制御手順を示したフロー図である。(第一実施例) 図5は追従車両の運転モードの学習処理手順を示したフロー図である。(第一実施例) 図6Aは運転モードの切り替えパラメータのバリエーションを示したフロー図である。 図6Bは運転モードの切り替えパラメータのバリエーションを示したフロー図である。 図6Cは運転モードの切り替えパラメータのバリエーションを示したフロー図である。 図6Dは運転モードの切り替えパラメータのバリエーションを示したフロー図である。 図7は運転モードの切り替えパラメータのバリエーションを示したフロー図である。(第二実施形態)
The accompanying drawings are included in the specification, constitute a part thereof, show an embodiment of the present invention, and are used to explain the principle of the present invention together with the description.
FIG. 1 is an explanatory diagram showing the configuration of the vehicle system. (First Example) FIG. 2 is an explanatory diagram showing a configuration for controlling the following vehicle. (First Example) FIG. 3 is an explanatory view showing the arrangement of sensors and control mechanisms of the following vehicle. (First Example) FIG. 4A is a flowchart showing a switching solution processing procedure of the driving mode of the following vehicle. (First Example) FIG. 4B is a flowchart showing a traveling control procedure of the following vehicle. (First Example) FIG. 5 is a flowchart showing the learning process procedure of the driving mode of the following vehicle. (First Example) FIG. 6A is a flowchart showing variations of operation mode switching parameters. FIG. 6B is a flowchart showing variations of operation mode switching parameters. FIG. 6C is a flowchart showing variations of operation mode switching parameters. FIG. 6D is a flowchart showing variations of operation mode switching parameters. FIG. 7 is a flowchart showing variations of operation mode switching parameters. (Second embodiment)
 [第一実施形態]
 本発明の実施形態として、自走車によりけん引可能で、なおかつ、自走車への追従機能を有する追従車両を説明する。この追従車両は、自走車にけん引されて走行する追従モードと、自走車にけん引されることなく自動運転機能により自走車を追走する自走モードという二つのモードの何れかで走行する。以下、この追従車両を中心として本実施形態を説明する。
[First embodiment]
As an embodiment of the present invention, a following vehicle that can be towed by a self-propelled vehicle and that has a function of following the self-propelled vehicle will be described. This follow-up vehicle runs in one of two modes: a follow-up mode in which it is towed by a self-propelled vehicle and a self-run mode in which the self-propelled vehicle is driven by an automatic driving function without being towed by the self-propelled vehicle. To do. Hereinafter, the present embodiment will be described focusing on the following vehicle.
 <車両の構成>
 図1に本実施形態に係る車両システムの構成を示す。本実施形態では動力付きの二輪車11が自走車である。図1には示していないが、自走車11は搭乗者により運転される二輪車である。また自走車11には、後述する追従車両13と通信するための通信部11aと、走行状態検知部11bとを備えている。走行状態検知部11bは、走行状態として例えば車両の傾きや加速度などを検知する。検知された走行状態情報は通信部11aにより追従車両に送信される。一方追従車両13は、けん引索12により自走車11にけん引される。けん引索12は例えばロープやワイヤなどで構成され、追従車両13をけん引するための十分な引張強度を有する。
<Vehicle configuration>
FIG. 1 shows a configuration of a vehicle system according to the present embodiment. In the present embodiment, the powered motorcycle 11 is a self-propelled vehicle. Although not shown in FIG. 1, the self-propelled vehicle 11 is a two-wheeled vehicle driven by a passenger. The self-propelled vehicle 11 includes a communication unit 11a for communicating with a follow-up vehicle 13 described later, and a traveling state detection unit 11b. The traveling state detection unit 11b detects, for example, the inclination or acceleration of the vehicle as the traveling state. The detected traveling state information is transmitted to the following vehicle by the communication unit 11a. On the other hand, the following vehicle 13 is pulled by the self-propelled vehicle 11 by the towing line 12. The towing line 12 is composed of, for example, a rope or a wire, and has a sufficient tensile strength for towing the following vehicle 13.
 追従車両13は、けん引索12を介して自走車11に結合される。自走車11とけん引索12との結合は取り外し可能である。追従車両13は、走行機構部13aと、積載部13bと、駆動輪13cと、操舵輪13dとを有する。走行機構部13aには走行駆動力の源であるエンジンと、エンジンにより駆動輪13cを駆動するための駆動機構と、さらに走行を制御するための制御部100(図3を参照して後述する。)等が含まれる。積載部13bは荷物を積載するための部分であり、図には示していないが蓋や固定ロープなど荷物を固定するための仕組みが用意されるのが望ましい。駆動輪13cと操舵輪13dは、いずれもけん引時には自由に回転して自走車11の負荷を軽減する。また操舵輪13dは、けん引時にはキャスターのようにその方向もけん引方向に応じて変わるよう構成される。なおエンジンとしては内燃機関のほか、電気モータや、内燃機関と電気モータのハイブリッドの動力ユニットを用いることもできる。 The following vehicle 13 is coupled to the self-propelled vehicle 11 via the towing line 12. The connection between the self-propelled vehicle 11 and the towing line 12 is removable. The following vehicle 13 includes a travel mechanism unit 13a, a loading unit 13b, a drive wheel 13c, and a steering wheel 13d. The travel mechanism unit 13a includes an engine that is a source of travel drive force, a drive mechanism that drives the drive wheels 13c by the engine, and a control unit 100 that controls travel (described later with reference to FIG. 3). ) Etc. are included. The loading portion 13b is a portion for loading a load, and it is desirable that a mechanism for fixing the load, such as a lid and a fixed rope, is prepared, although not shown in the drawing. Both the driving wheel 13c and the steering wheel 13d rotate freely during towing to reduce the load on the self-propelled vehicle 11. The steering wheel 13d is configured to change its direction according to the towing direction like a caster when towing. In addition to the internal combustion engine, an electric motor or a hybrid power unit of the internal combustion engine and the electric motor can be used as the engine.
 車両システムの基本構成は上述のとおりであるが、けん引索12は、金属パイプなどの剛性の高いけん引バーなどの接続部材に代えてもよい。この場合、けん引バーの両端または片端には、自在に方向を変えられるよう例えば自在継ぎ手などが設けられることが望ましい。 The basic configuration of the vehicle system is as described above, but the towing line 12 may be replaced with a connecting member such as a towing bar having high rigidity such as a metal pipe. In this case, it is desirable that, for example, a universal joint or the like is provided at both ends or one end of the tow bar so that the direction can be freely changed.
 なお、図1では追従車両は小径の車輪に比較的大きな上部構造が載った構成となっているが、走行速度や制動力などを考慮して、より大径で幅広の中空ゴムの車輪を採用してもよい。また、走行時の安定性のために、駆動輪13cと操舵輪13dの前後の間隔や、左右の間隔をより広くしてもよい。また走行の安定のために走行輪を緩衝部材で支持してもよい。すなわち一般的な自動車と同様のシャシーを有していてもよい。 In FIG. 1, the following vehicle has a structure in which a relatively large superstructure is mounted on a small-diameter wheel. However, in consideration of traveling speed and braking force, a larger-diameter and wider hollow rubber wheel is adopted. May be. In addition, the distance between the front and rear of the driving wheel 13c and the steering wheel 13d and the distance between the left and right may be increased for stability during traveling. Moreover, you may support a driving | running | working wheel with a buffer member for stability of driving | running | working. That is, you may have the chassis similar to a common motor vehicle.
 <従属車両の制御部の構成>
 図2に追従車両13の内部の一例、特に走行機構部13aについて説明する図を示す。図2は追従車両13を上面あるいは下面から見た図であり、向かって右側が前方すなわち自走車11の側である。機構部13aには、その前方を中心として一定の範囲をカバーするレーダ30とカメラ40とが設けられている。また、路面に向けて路面センサ50が設けられている。路面センサ50は、進行方向に向かって一定の距離の路面の状態を検知するための例えばカメラやレーダにより構成される。なお以下では、レーダ30、カメラ40、路面センサ50をまとめて外部センサと呼ぶことがある。外部センサは制御部100に接続されて、出力信号が制御部100に伝達される。
<Configuration of subordinate vehicle control unit>
FIG. 2 shows an example of the inside of the following vehicle 13, in particular, a diagram for explaining the traveling mechanism unit 13 a. FIG. 2 is a view of the following vehicle 13 as viewed from the upper surface or the lower surface. The mechanism unit 13a is provided with a radar 30 and a camera 40 that cover a certain range centering on the front thereof. A road surface sensor 50 is provided toward the road surface. The road surface sensor 50 is configured by, for example, a camera or a radar for detecting the state of a road surface at a certain distance in the traveling direction. Hereinafter, the radar 30, the camera 40, and the road surface sensor 50 may be collectively referred to as external sensors. The external sensor is connected to the control unit 100 and an output signal is transmitted to the control unit 100.
 制御部100には走行駆動力出力装置72、ステアリング装置74、ブレーキ装置76が接続され、それら装置を制御する。走行駆動力出力装置72は例えば電気モータや内燃機関などのエンジンであり、制御部100の制御の下で駆動輪13cを駆動して追従車両13を走行させる。走行駆動力出力装置72は、たとえば動力が電気モータであれば電流を制御し、また内燃機関であれば、吸入空気量、スロットル開度、アクセル開度その他の車両情報に基づき、燃料噴射制御、点火時期制御、電子制御スロットル弁の開度制御等の主要な制御を行う。 The controller 100 is connected with a driving force output device 72, a steering device 74, and a brake device 76, and controls these devices. The traveling driving force output device 72 is an engine such as an electric motor or an internal combustion engine, for example, and drives the driving wheel 13 c under the control of the control unit 100 to cause the following vehicle 13 to travel. The driving force output device 72 controls the current if the power is an electric motor, for example, and if it is an internal combustion engine, the fuel injection control based on the intake air amount, the throttle opening, the accelerator opening, and other vehicle information. Main controls such as ignition timing control and electronic throttle valve opening control.
 ステアリング装置74は、制御部100の制御の下で操舵輪13dの舵角(或いは方向)を変えることで追従車両13の進行方向を制御する。操舵輪の舵角は、前を走行する自走車11の進行方向に応じて決められる。ブレーキ装置76は、走行制御部112から、各輪のブレーキ力が入力された場合には、該ブレーキ力に基づいて各輪のブレーキ液圧を算出し、ブレーキ駆動部を作動させる。それにより制御部100の制御の下で駆動輪13c及び操舵輪13dを制動し、追従車両13を減速させ、あるいは停止させる。 The steering device 74 controls the traveling direction of the following vehicle 13 by changing the steering angle (or direction) of the steering wheel 13d under the control of the control unit 100. The steering angle of the steered wheels is determined according to the traveling direction of the self-propelled vehicle 11 traveling in front. When the brake force of each wheel is input from the traveling control unit 112, the brake device 76 calculates the brake fluid pressure of each wheel based on the brake force, and operates the brake drive unit. Accordingly, the driving wheel 13c and the steering wheel 13d are braked under the control of the control unit 100, and the following vehicle 13 is decelerated or stopped.
 <運転制御システム1の構成>
 図3に運転制御システム1の構成例を示す。運転制御システム1は、制御部100にセンサ類と駆動用装置の制御系とを接続している構成される。制御部100は例えばコンピューターとそれが実行するプログラム及びメモリを中心として構成されてもよい。以下、制御部100を中心とした自動運転のための制御構成を簡単に説明する。なお自動運転は、たとえば特許文献2などに記載されたような技術を用いて行うこともできるが、本実施形態の追従車両13は、前走する自走車11に追従できる程度の限定的な自動運転ができればよい。
<Configuration of operation control system 1>
FIG. 3 shows a configuration example of the operation control system 1. The operation control system 1 is configured by connecting sensors and a control system of a driving device to the control unit 100. For example, the control unit 100 may be configured with a computer, a program executed by the computer, and a memory. Hereinafter, a control configuration for automatic operation centering on the control unit 100 will be briefly described. In addition, although automatic driving | running | working can also be performed using the technique as described in patent document 2, etc., for example, the following vehicle 13 of this embodiment is limited to such an extent that it can follow the self-propelled vehicle 11 which runs ahead. It suffices if automatic operation is possible.
 図3において、制御部100には、走行駆動力出力装置72、ブレーキ装置76、ステアリング装置74が、駆動用装置の制御系として接続されている。また走行制御装置112には、レーダ30やカメラ40、路面センサ50を含むセンサ類から、外部環境に関する信号が入力される。これらの外部環境を検知するためのデバイスを外部検知ユニットと呼ぶこともある。本実施形態では追従車両13が追従対象である自走車11を認識することが必要なので、カメラ40は、追従車両13の前方を中心として、追従車両13が自走車11の真後ろから一定の範囲内で移動しても、自走車11を撮影できるように配置される。またカメラ40は1台としているが、撮影範囲をカバーするために複数台用いてもよい。追従対象の自走車11は、その画像中の特徴により認識されるが、そのためにたとえば予め定めたパターンを描いたシール等を自走車11の後部に貼付しておいてもよい。 3, a traveling driving force output device 72, a brake device 76, and a steering device 74 are connected to the control unit 100 as a control system of the driving device. In addition, signals related to the external environment are input to the travel control device 112 from sensors including the radar 30, the camera 40, and the road surface sensor 50. Devices for detecting these external environments are sometimes called external detection units. In the present embodiment, since it is necessary for the following vehicle 13 to recognize the self-propelling vehicle 11 that is the object to be followed, the camera 40 is centered on the front of the following vehicle 13 and the following vehicle 13 is constant from behind the self-propelling vehicle 11. Even if it moves within the range, it is arranged so that the self-propelled vehicle 11 can be photographed. Although one camera 40 is used, a plurality of cameras 40 may be used to cover the shooting range. Although the self-propelled vehicle 11 to be followed is recognized by the feature in the image, for example, a sticker or the like depicting a predetermined pattern may be attached to the rear portion of the self-propelled vehicle 11.
 姿勢センサ60は、追従車両13の方向や加速度、角加速度、傾斜等の、追従車両の姿勢を検知する自車状態検知ユニットであり、検知した状態を示す出力信号は制御部100に入力される。路面センサ50は、路面の状態を検知する検知ユニットであり、まさに走行している路面の状態を示す信号が制御部100に入力される。検知される路面の状態は、路面の摩擦係数に係る状態たとえばその凹凸の程度や、路面の濡れなどがあり得る。GPS受信機70はGPS衛星からの信号を受信する。通信ユニット65は、自走車側の通信部11aと通信する。通信ユニット65は自走車11から送信される走行状態情報を受信することができる。 The posture sensor 60 is a host vehicle state detection unit that detects the posture of the following vehicle such as the direction, acceleration, angular acceleration, and inclination of the following vehicle 13, and an output signal indicating the detected state is input to the control unit 100. . The road surface sensor 50 is a detection unit that detects the state of the road surface, and a signal that indicates the state of the road surface that is running is input to the control unit 100. The detected road surface state may be a state related to the friction coefficient of the road surface, for example, the degree of unevenness thereof, or the wetness of the road surface. The GPS receiver 70 receives signals from GPS satellites. The communication unit 65 communicates with the communication unit 11a on the self-propelled vehicle side. The communication unit 65 can receive the traveling state information transmitted from the self-propelled vehicle 11.
 さて制御部100ではこれら走行状態情報や外部環境等の情報を入力として、主として走行の制御を行う。制御部100において、自車状態認識部101は、たとえば姿勢センサ60から入力される加速度や各加速度、方向あるいは路面センサ50から入力される路面状態の信号に基づいて、追従車両13自身の状態を特定する。特定される状態は所定周期で更新され、記憶部130等に記憶される。特定される情報には、たとえば最新の時点における速度や加速度、進行方向、路面状態等を示す情報に加えて、制動が開始された時点からの速度の変化などがある。 Now, the control unit 100 mainly controls the driving by using the driving state information and the external environment as input. In the control unit 100, the own vehicle state recognition unit 101 determines the state of the following vehicle 13 based on, for example, an acceleration input from the attitude sensor 60, each acceleration, direction, or a road surface state signal input from the road surface sensor 50. Identify. The specified state is updated at a predetermined cycle and stored in the storage unit 130 or the like. The specified information includes, for example, a change in speed from the time when braking is started, in addition to information indicating speed, acceleration, traveling direction, road surface condition, and the like at the latest time.
 自車位置認識部102にはGPS受信機70からGPS信号が入力される。自車位置認識部102は、たとえばGPS信号から特定される自車位置と地図情報132とを照合して、地図上に置ける自車位置を特定する。地図上における自車位置を特定することで、次のカーブの入り口までの距離やそのカーブの程度などの道路状況のほか、たとえば地図上の位置毎に関連づけて登録されている情報を取得することができる。上述した路面状態を地図に関連づけて登録しておけば、地図情報から路面状態を取得することもできる。 A GPS signal is input from the GPS receiver 70 to the vehicle position recognition unit 102. The own vehicle position recognizing unit 102 collates the own vehicle position specified from the GPS signal with the map information 132, for example, and specifies the own vehicle position that can be placed on the map. By identifying the location of the vehicle on the map, you can obtain information registered in association with each location on the map, for example, in addition to the road conditions such as the distance to the next curve entrance and the degree of the curve. Can do. If the road surface state described above is registered in association with the map, the road surface state can also be acquired from the map information.
 前走車認識部103は、カメラ40で撮影した車両の外部環境の画像を処理して外部環境、特に直前を走行する自走車11を認識することができる。前走車認識部103は、カメラ40に代えて、あるいはカメラ40とともにレーダ30による検知結果を前走車の認識のために利用してもよい。特に制動時には自走車11との車間距離を維持する必要から、距離の特定のためにレーダ30による距離測定結果を援用することができる。なお前走車認識部には、カメラ40やレーダ30などの外部検知ユニットを含めることもある。 The front-running vehicle recognition unit 103 can recognize an external environment, particularly the self-propelled vehicle 11 traveling immediately before by processing an image of the external environment of the vehicle photographed by the camera 40. The preceding vehicle recognition unit 103 may use the detection result of the radar 30 instead of the camera 40 or together with the camera 40 for recognition of the preceding vehicle. In particular, since it is necessary to maintain the inter-vehicle distance from the self-propelled vehicle 11 during braking, the distance measurement result by the radar 30 can be used for specifying the distance. The forward vehicle recognition unit may include an external detection unit such as the camera 40 or the radar 30.
 ここで、カメラ40は、カメラ本体と、画像処理部とを一体化して構成されていてもよいし、制御部100により画像処理を行ってもよい。またカメラ40はステレオカメラであることが望ましい。ステレオカメラを用いれば、画像処理によって、それぞれのカメラの視差に基づいて被写体までの距離を推定できる。前走車認識部103は、ステレオカメラにより認識した立体物のデータ等に基づいて自車走行路上の先行車を検出し、自車両と先行車との車間距離、自車両に対する先行車の車速(相対速度)、先行車の加速度(減速度)等を演算することもでき、先行車情報として走行制御部12へ出力する。 Here, the camera 40 may be configured by integrating the camera body and the image processing unit, or the control unit 100 may perform image processing. The camera 40 is preferably a stereo camera. If a stereo camera is used, the distance to the subject can be estimated based on the parallax of each camera by image processing. The preceding vehicle recognition unit 103 detects the preceding vehicle on the own vehicle traveling path based on the data of the three-dimensional object recognized by the stereo camera, the distance between the own vehicle and the preceding vehicle, the vehicle speed of the preceding vehicle relative to the own vehicle ( Relative speed), acceleration (deceleration) of the preceding vehicle, and the like can also be calculated and output to the travel control unit 12 as preceding vehicle information.
 走行制御部112は、自車状態認識部101、自車位置認識部102、前走車認識部103の一部または全部から入力される情報を用いて、追従車両13の走行を制御する。走行は運転モードごとに制御され、運転モードは走行制御部112が有する運転モード決定部1121により決定される。運転モードの決定の基準としては様々な情報を利用できるが、本例では先行車である自走車11から受信した走行状態情報を用いる。運転モードには、自車の有する動力を用いて自律的に運転を制御する自走モードと、先行車にけん引されて走行する追従モードとが含まれる。ただし、追従モードにおいても、ロープやワイヤ等の柔軟な素材で先行車に結合される場合には、追突を防止するためにブレーキの制御は先行車の走行状態に応じて行われる。決定された運転モードは運転モード記憶部1122に記憶される。本例では運転モード記憶部1122には、追従車両13が動作している現在の運転モードと、運転モードが更新された際には更新後の最新の運転モードとが記憶される。 The traveling control unit 112 controls traveling of the following vehicle 13 by using information input from part or all of the own vehicle state recognition unit 101, the own vehicle position recognition unit 102, and the preceding traveling vehicle recognition unit 103. The travel is controlled for each operation mode, and the operation mode is determined by the operation mode determination unit 1121 included in the travel control unit 112. Although various information can be used as a reference for determining the driving mode, in this example, traveling state information received from the self-propelled vehicle 11 which is a preceding vehicle is used. The driving mode includes a self-running mode in which driving is autonomously controlled using the power of the own vehicle and a follow-up mode in which the vehicle is towed by a preceding vehicle. However, even in the follow-up mode, when a flexible material such as a rope or wire is used to join the preceding vehicle, the brake is controlled according to the traveling state of the preceding vehicle in order to prevent a rear-end collision. The determined operation mode is stored in the operation mode storage unit 1122. In the present example, the operation mode storage unit 1122 stores the current operation mode in which the following vehicle 13 is operating and the latest operation mode after the update when the operation mode is updated.
 記憶部130はメモリあるいはストレージであり、運転制御のために用いられる地図情報132と、運転モードを決定するための、たとえば先行車の加速度や傾斜あるいはその両方などの走行状態情報や、走行状態情報をパラメータとして決定された運転モード、その良否の評価を示すラベルなどが蓄積された切り替え基準情報133とを格納している。 The storage unit 130 is a memory or a storage, and includes map information 132 used for driving control, driving state information such as acceleration and / or inclination of a preceding vehicle, and driving state information for determining a driving mode. The switching reference information 133 in which the operation mode determined using as a parameter, the label indicating the evaluation of the quality, and the like are stored is stored.
 学習制御部140は、切り替え基準情報133に蓄積された情報、あるいは入力されたラベル(良否情報)を参照して、運転モードの決定の基準を更新し、改善する。学習制御部140による処理手順は、その一例を図5に示したが、たとえばクラウドにより提供されている機械学習などの人工知能のサービスを利用して実現してもよい。その場合には、インターネットに接続するための通信機能をさらに有する必要がある。 The learning control unit 140 updates and improves the criteria for determining the operation mode with reference to the information accumulated in the switching criterion information 133 or the input label (good / bad information). An example of the processing procedure performed by the learning control unit 140 is shown in FIG. 5, but may be realized by using an artificial intelligence service such as machine learning provided by the cloud. In that case, it is necessary to further have a communication function for connecting to the Internet.
 以上のように、運転制御システム1の中心となる走行制御部100は、追従走行を自律的に行う自走モードで走行するか、それとも動力を用いない追従モードでけん引に任せるかを、先行する自走車の走行状態に応じて決定する。特に、自走モードで走行する際には、先行車両に対する追従精度を確保しつつ車体挙動の変化を抑制するため、各センサ30,40,50,60からの情報や、位置情報等に基づいて、操舵制御と減速制御との協調制御を最適化して実行する。制御部100にはこのほか、たとえば操作者が情報等を入力するための入力デバイス78を備えている。 As described above, the traveling control unit 100 that is the center of the driving control system 1 precedes whether the vehicle travels in the self-running mode in which the follow-up traveling is autonomous or is left to the towing in the follow-up mode that does not use power. Determined according to the traveling state of the self-propelled vehicle In particular, when traveling in the self-propelled mode, based on information from each sensor 30, 40, 50, 60, position information, etc., in order to suppress changes in vehicle body behavior while ensuring tracking accuracy with respect to the preceding vehicle. Then, the cooperative control between the steering control and the deceleration control is optimized and executed. In addition, the control unit 100 includes an input device 78 for an operator to input information and the like.
 なお、走行駆動力制御装置72による駆動力の制御やステアリング装置74による舵角の制御、ブレーキ装置76による制動の制御の詳細については、たとえば特許文献2に記載されたような構成および方法で行うことができるので、ここでは詳細についての説明は割愛する。 The details of the driving force control by the traveling driving force control device 72, the steering angle control by the steering device 74, and the braking control by the brake device 76 are performed, for example, by the configuration and method described in Patent Document 2. I won't go into detail here.
 <運転モードの切り替え>
 次に制御部100、特に走行制御部112による制御の手順の例を、図4Aおよび図5を参照して説明する。図4Aは、運転モードの切り替え手順の一例を示す。制御部100が、プログラムをプロセッサにより実行することで実現される場合には、図4Aの手順はそのプロセッサによって実行されることになる。これは他のフローチャートについても同様である。
<Switching operation mode>
Next, an example of a control procedure by the control unit 100, in particular, the traveling control unit 112 will be described with reference to FIGS. 4A and 5. FIG. 4A shows an example of an operation mode switching procedure. When the control unit 100 is realized by executing a program by a processor, the procedure of FIG. 4A is executed by the processor. The same applies to the other flowcharts.
 図4Aにおいて、走行制御部112は、走行状態情報を取得し(S401)、取得した走行状態情報から評価値を生成する。生成した評価値は、運転モードを自走モードか従動モードかのいずれに設定するための指標である。評価値の基となる走行状態情報としては、この例では、自走車11から受信した、自走車11の走行状態を示す走行状態情報である。またこのとき、評価値の生成のために使用したパラメータ(例えば先行車の加速度と車体の傾斜あるいはそのいずれかなど)を、評価値と関連付けて切り替え基準情報133に格納しておく。 4A, the traveling control unit 112 acquires traveling state information (S401), and generates an evaluation value from the acquired traveling state information. The generated evaluation value is an index for setting the operation mode to either the self-running mode or the driven mode. In this example, the traveling state information that is the basis of the evaluation value is traveling state information that is received from the traveling vehicle 11 and indicates the traveling state of the traveling vehicle 11. At this time, the parameters used for generating the evaluation value (for example, the acceleration of the preceding vehicle and / or the inclination of the vehicle body) are stored in the switching reference information 133 in association with the evaluation value.
 本例では、生成される評価値は、基準となる情報の値をパラメータとして、それぞれに対応する重みを乗じてそれを加算する式により算出される。具体的には評価値=Σ(wi×xi)である。ここでxiがパラメータ、wiがその重みである。さらに定数であるバイアス値を加算してもよい。基準となる情報は、たとえば加速度と車体の傾き或いはそれらのいずれかを含む。また重み付けは、たとえば蓄積した走行状態情報などを教師データとする機械学習により更新することで、運転モードの切り替えのタイミングをより好適なタイミングへと改善することができる。本例では学習前の重みの初期値は、たとえば他の車両のデータから学習した値や、またたとえば全て1とするなど、適当に設定されてよい。また評価値をただ一つのパラメータから生成する場合には、パラメータに乗ずる重みの代わりに基準値に重みを乗じ、その重みを学習により更新してもよい。 In this example, the generated evaluation value is calculated by using an information value as a reference as a parameter, multiplied by a corresponding weight, and added. Specifically, evaluation value = Σ (wi × xi). Here, xi is a parameter, and wi is its weight. Further, a constant bias value may be added. The reference information includes, for example, acceleration and / or inclination of the vehicle body. Moreover, the weighting can be improved to a more suitable timing by updating the driving mode switching by machine learning using, for example, accumulated traveling state information as teacher data. In this example, the initial value of the weight before learning may be appropriately set, for example, a value learned from data of another vehicle, or all 1 for example. When the evaluation value is generated from only one parameter, the reference value may be multiplied by the weight instead of the weight multiplied by the parameter, and the weight may be updated by learning.
 次にステップS402において、算出した評価値を所定の基準値と比較する。基準値はたとえば、自走モードと従動モードとの境界付近の走行状態情報を想定し、その値と各走行状態情報の重みを初期値として算出した評価値と同程度の値となるように決めればよい。また基準値は一つであってもよいが、複数であってもよい。その場合には、自走モードから従動モードへ移行するための基準値と、従動モードから自走モードへと移行するための基準値とを異なる値としてもよい。たとえば評価値が第一の基準値を超えた場合に一方の運転モードに移行し、第二の基準値を下回った場合に他方の運転モードに移行するなら、第一の基準値>第二の基準値としてもよい。このようにすることで、切り替えた運転モードの持続性を高めることができ、頻繁な運転モードの切り替えを防止できる。 Next, in step S402, the calculated evaluation value is compared with a predetermined reference value. For example, the reference value is assumed to be the same value as the evaluation value calculated by assuming the running state information near the boundary between the self-running mode and the driven mode and using the value and the weight of each running state information as an initial value. That's fine. Further, the reference value may be one, but may be plural. In that case, the reference value for shifting from the free-running mode to the driven mode may be different from the reference value for shifting from the driven mode to the free-running mode. For example, when the evaluation value exceeds the first reference value, the operation mode shifts to one operation mode, and when the evaluation value falls below the second reference value, the operation mode shifts to the other operation mode. It may be a reference value. By doing in this way, the sustainability of the switched operation mode can be improved and frequent switching of the operation mode can be prevented.
 次にステップS403において、運転モードを決定する。この例では、車体の傾斜が大きいか、あるいは、負の加速度が一定以上であれば、運転モードを自走モードとする。あるいは両方の条件を共に満たしている場合に自走モードとする。すなわち、評価値が基準値を超えたなら自走モードとする。この時にはステップS404に分岐する。それ以外の場合には運転モードは従動モードでありステップS405に分岐する。なお評価値から決定される運転モードも評価値を算出する基になったパラメータと関連付けて切り替え基準情報133に格納しておく。なお図5で説明する、運転モードの切り替えに対する運転者の評価を示す良否情報も、評価値及び運転モードに関連付けて格納される。これら関連付けられた情報の単位を項目と呼ぶことにする。一つの項目に関連する走行状態応報と運転モードと良否情報とが含まれる。切り替え基準情報133に格納されたこれら項目は、運転モードが切り替えられるつど蓄積されていく。 Next, in step S403, the operation mode is determined. In this example, the driving mode is set to the self-running mode if the inclination of the vehicle body is large or the negative acceleration is equal to or greater than a certain value. Alternatively, the self-run mode is set when both conditions are satisfied. That is, if the evaluation value exceeds the reference value, the self-running mode is set. At this time, the process branches to step S404. In other cases, the operation mode is the driven mode, and the process branches to step S405. The operation mode determined from the evaluation value is also stored in the switching reference information 133 in association with the parameter that is the basis for calculating the evaluation value. In addition, the quality information which shows the driver | operator's evaluation with respect to switching of the driving mode demonstrated in FIG. 5 is also linked | related with the evaluation value and driving mode, and is stored. These associated information units are referred to as items. A running condition response, an operation mode, and pass / fail information related to one item are included. These items stored in the switching reference information 133 are accumulated each time the operation mode is switched.
 ステップS404では、運転モード記憶部記憶部1122に最新の運転モードとして自走モードを設定する。この後走行制御部112は自走モードでの走行制御を行うことになる。一方ステップS405では、運転モード記憶部記憶部1122に最新の運転モードとして従動モードを設定する。この後走行制御部102は従動モードでの走行制御を行うことになる。自走モードでは、基本的には、カメラ40により撮影した画像から前走車認識部103により自走車11認識し、走行制御部112は、認識した自走車11を追尾するように走行を制御する。 In step S404, the self-running mode is set as the latest driving mode in the driving mode storage unit 1122. Thereafter, the traveling control unit 112 performs traveling control in the self-running mode. On the other hand, in step S405, the driven mode is set as the latest operation mode in the operation mode storage unit 1122. Thereafter, the traveling control unit 102 performs traveling control in the driven mode. In the self-propelled mode, basically, the front-running vehicle recognition unit 103 recognizes the self-propelled vehicle 11 from the image captured by the camera 40, and the travel control unit 112 travels so as to track the recognized self-propelled vehicle 11. Control.
 運転モードの設定を終えたなら、所定時間待機した後、ステップS401へ進む。ここでいう所定時間は0であってもよい。これによって走行状態の変化を周期的に繰り返し監視し、走行状態に対応した運転モードを設定することができる。 If the operation mode has been set, the process proceeds to step S401 after waiting for a predetermined time. The predetermined time here may be zero. As a result, it is possible to periodically monitor changes in the running state and set an operation mode corresponding to the running state.
 <走行制御手順>
 図4Bは、運転モードが設定された際の走行制御部112による走行制御手順を示す。走行制御のことを運転制御とも呼ぶ。図4Bの手順は図4Aとは非同期に、周期的に実行される。まず運転モード記憶部1122に記憶された最新の運転モードを、これも運転モード記憶部1122に記憶された、現在の運転モードと比較する(S411)。一致すれば運転モードは変化していないものと判断して図4Bの処理は終了とする。一致しなければ、運転モードが更新されたものとして、現在の運転モードを最新の運転モードで書き換える(S412)。これにより現在の運転モードが更新される。
<Progression control procedure>
FIG. 4B shows a travel control procedure by the travel control unit 112 when the operation mode is set. The travel control is also called operation control. The procedure of FIG. 4B is periodically executed asynchronously with FIG. 4A. First, the latest operation mode stored in the operation mode storage unit 1122 is compared with the current operation mode also stored in the operation mode storage unit 1122 (S411). If they match, it is determined that the operation mode has not changed, and the processing in FIG. 4B ends. If not, the current operation mode is rewritten with the latest operation mode, assuming that the operation mode has been updated (S412). As a result, the current operation mode is updated.
 次に現在の運転モードがいずれのモードであるか判定する(S413)。自走モードと判定された場合には、運転モードは従動モードから自走モードへと変更されたので、自走モードに応じて各装置の制御を開始する(S414)。この後、走行駆動力の出力を開始する(S415)。すなわち、本例では動力である電気モータの駆動を開始する。これにより自走モードでの運転制御が開始され、運転制御システム1は、各種センサ等からの入力に従って、駆動と制動、および操舵を制御して、先行車を追跡するように追従車両13を制御する。 Next, it is determined which mode is the current operation mode (S413). If it is determined as the self-running mode, the operation mode is changed from the driven mode to the self-running mode, and thus control of each device is started according to the self-running mode (S414). Thereafter, output of the driving force is started (S415). That is, in this example, driving of the electric motor that is power is started. As a result, the driving control in the self-running mode is started, and the driving control system 1 controls the following vehicle 13 so as to track the preceding vehicle by controlling driving, braking, and steering in accordance with inputs from various sensors and the like. To do.
 自走モードでは、カメラ40及び/又はレーダ30により先行車である自走車11を画像上で捕捉し、それに追従するように走行を制御する。その際に、けん引索12には、自走車11の運転に制約が掛からないよう、けん引索12の自重によるもの以外の張力が掛からないように運転が制御される。そのためにはたとえば、レーダ30やカメラ40により先行車との距離を測定し、距離が一定の範囲に収まるよう走行駆動力とブレーキとステアリングとを制御する。またたとえば、先行する自走車11との相対速度をさらに測定し、相対速度が負になれば加速し、正になれば減速するよう制御する。加速および減速の程度は、相対速度の絶対値に応じた値とする。ステアリングについては、たとえば追従の目標となるオブジェクトをカメラ40の撮影画像から特定し、その動きに追従するように、その時の速度に応じた舵角で操舵輪13dを制御する。 In the self-propelled mode, the self-propelled vehicle 11 that is the preceding vehicle is captured on the image by the camera 40 and / or the radar 30, and the traveling is controlled so as to follow it. At that time, the operation is controlled so that no tension other than that due to the weight of the towing line 12 is applied to the towing line 12 so that the operation of the self-propelled vehicle 11 is not restricted. For this purpose, for example, the distance to the preceding vehicle is measured by the radar 30 or the camera 40, and the driving force, the brake, and the steering are controlled so that the distance is within a certain range. Further, for example, the relative speed with respect to the preceding self-propelled vehicle 11 is further measured, and control is performed so as to accelerate when the relative speed becomes negative and decelerate when the relative speed becomes positive. The degree of acceleration and deceleration is a value according to the absolute value of the relative speed. For steering, for example, an object to be followed is specified from a captured image of the camera 40, and the steered wheel 13d is controlled at a steering angle corresponding to the speed at that time so as to follow the movement.
 一方現在の運転モードが従動モードであると判定された場合には、運転モードは自走モードから従動モードへと変更されたので、まず電気モータなどの走行駆動出力を停止する(S416)。そして駆動輪13cおよび操舵輪13dを解放し(S417)、従動モードに応じた各装置の制御を開始する(S418)。すなわち、本例では、従動モードでもブレーキの制御を行うこととしているので、走行制御部112は、ブレーキ装置76の制御を続ける。ブレーキの制御はたとえば、レーダ30やカメラ40により先行車との距離を測定し、所定距離以下になったなら、制動をかけるよう走行制御部112はブレーキ装置76を制御する。あるいは、先行車に対する追従車両13の相対速度を測定し、相対速度がプラスになったなら、制動をかけるよう走行制御部112はブレーキ装置76を制御する。制動の強さを、相対速度の大きさに応じて制御してもよい。 On the other hand, if it is determined that the current driving mode is the driven mode, the driving mode is changed from the self-running mode to the driven mode, and thus the driving drive output of the electric motor or the like is first stopped (S416). Then, the driving wheel 13c and the steering wheel 13d are released (S417), and control of each device according to the driven mode is started (S418). That is, in this example, since the brake is controlled even in the driven mode, the traveling control unit 112 continues to control the brake device 76. For the brake control, for example, the distance from the preceding vehicle is measured by the radar 30 or the camera 40, and the traveling control unit 112 controls the brake device 76 to apply the brake when the distance is equal to or less than a predetermined distance. Alternatively, the relative speed of the following vehicle 13 with respect to the preceding vehicle is measured, and when the relative speed becomes positive, the traveling control unit 112 controls the brake device 76 to apply the brake. The strength of braking may be controlled according to the magnitude of the relative speed.
 さらに、ブレーキの制御に加えて、従動モードでもステアリングの制御を行ってもよい。けん引索12で追従車両13をけん引すると、追従車両13の動きの自由度が大きく、車線を逸脱することもないとは言えない。そこで、走行駆動力を停止したままで、ステアリングの制御を自走モードと同じように行ってもよい。なおけん引索12に代えて剛性の高い棒などを使用する場合にはブレーキの制御をおこなわなくともよい。 Furthermore, in addition to the brake control, the steering may be controlled in the driven mode. If the follower vehicle 13 is towed by the towing line 12, the follower vehicle 13 has a large degree of freedom of movement and cannot be said to deviate from the lane. Therefore, the steering control may be performed in the same manner as in the self-running mode while the driving force is stopped. In addition, when using a rigid rod instead of the towing line 12, it is not necessary to control the brake.
 いったん運転モードが決まったなら、新たな運転モードが設定されるまでその運転モードで制御される。 Once the operation mode is determined, the operation mode is controlled until a new operation mode is set.
 <運転モードの切り替え条件の学習>
 図4Aに示したように、運転モードは、算出した評価値が一定の基準を満たした場合に切り替えられる。この評価値を算出するための重み付けを、実際に設定された運転モードの切り替え条件(あるいは切り替えタイミング)の良否に応じて学習させ、改善するための手順を図5に示す。切り替え条件の良否は、たとえば自走車11の運転者が入力部から入力し、それを通信部11aで追従車両13の通信ユニット65を介して制御部100に送信する。この良否の評価は、教師データのラベルとして用いられる。制御部100の学習制御部140が、その入力値を用いて図5の手順を実行する。学習制御部140がプロセッサによりプログラムを実行することで実現される場合には、そのプロセッサが図5の手順の実行主体となる。なおこの手順は入力がある都度実時間で行ってもよいし、入力値を評価値のパラメータと関連付けて記憶部130に蓄積しておき、バッチで行ってもよい。
<Learning operation mode switching conditions>
As shown in FIG. 4A, the operation mode is switched when the calculated evaluation value satisfies a certain standard. FIG. 5 shows a procedure for learning and improving the weighting for calculating the evaluation value according to the quality of the operation mode switching condition (or switching timing) actually set. For example, the driver of the self-propelled vehicle 11 inputs the switching condition from the input unit, and transmits it to the control unit 100 via the communication unit 65 of the following vehicle 13 by the communication unit 11a. This pass / fail evaluation is used as a label for teacher data. The learning control unit 140 of the control unit 100 executes the procedure of FIG. 5 using the input value. When the learning control unit 140 is realized by executing a program by a processor, the processor becomes an execution subject of the procedure of FIG. Note that this procedure may be performed in real time whenever an input is made, or may be performed in batch by storing the input value in the storage unit 130 in association with the parameter of the evaluation value.
 まず通信ユニット65が、自走車11の運転者の操作した良否選択の入力値(すなわちラベル)を受信する(S501)。このラベルは、最後に行われた運転モードの切り替えに対する運転者の評価であり、教師データすなわち切り替え基準情報133に蓄積されるパラメータから得られる運転モードが正解か否かを判定するために利用される。なお図5の処理はこのラベルの受信をトリガとして開始されてもよい。 First, the communication unit 65 receives an input value (that is, a label) for pass / fail selection operated by the driver of the self-propelled vehicle 11 (S501). This label is an evaluation of the driver with respect to the last switching of the driving mode, and is used to determine whether or not the driving mode obtained from the parameters accumulated in the teacher data, that is, the switching reference information 133 is correct. The Note that the processing in FIG. 5 may be started by receiving this label as a trigger.
 次に、切り替え基準情報133を参照して、現在の運転モードの基となった最新の切り替え基準情報に関連づけて、入力されたラベルを格納する(S502)。 Next, referring to the switching criterion information 133, the input label is stored in association with the latest switching criterion information that is the basis of the current operation mode (S502).
 次に入力されたラベルの値を判定する(S503)。評価が「良」であれば、現在の運転モードへの切り替えは正解であり、この場合過去の運転モードも正解であるはずなので、評価式を変える必要はない。そこで処理は終了する。 Next, the value of the input label is determined (S503). If the evaluation is “good”, switching to the current operation mode is correct, and in this case, the past operation mode should also be correct, so there is no need to change the evaluation formula. Thus, the process ends.
 一方ラベルが「否」の場合には、現在の運転モードへの切り替え、あるいは切り替えのタイミングは正解ではない。そこで評価値の生成式における各パラメータの係数すなわち重みを再計算する(S504)。なお評価値の計算式においてバイアス値(すなわち定数)を加算している場合にはそのバイアス値をも重みに含め、各パラメータに乗じる重みをまとめて重みベクトルとも呼ぶ。ここで重みベクトルの変更は、パラメータxiに対応する重みをwiと表せば、たとえばwi←wi+Lρxiで行われる。ここでLは1とし、ρは小さな値の正の定数である。ρは変更のステップを決める値であり、小さすぎると適正な重みベクトルに達するまでの計算量が増え、大きすぎると過度な変更が施される可能性がある。ρは、一般的にはパラメータごとに異なる値であってもよいし、正負が一致していなくともよい。学習により重みを小さくしたいパラメータについては負の値とし、大きくしたい値については正の値とする。本例では正の値とする。またステップS504では評価値算出に用いられるパラメータが複数であれば、その全ての重みについて再計算される。これによって重みはわずかに大きくなり再計算される評価値は大きくなる。したがって、本例では重みの変更によって、より小さい傾き、あるいはより小さい加速度で、自走モードに切り替わるようになる。そのようにするのは、運転者が「否」とラベル付けするのは、自走モードへの切り替えが遅すぎるか、あるいは従動モードへの切り替えが早すぎて、自由な走行を妨害されたと感じる場合と考えられるためである。これは基準値に対して評価値が小さすぎる場合に生じるため、本例では評価値を増大させる方向で重みを再計算する。この説明は、評価値が加速度または車体傾斜を例にしているが、他の情報に基づく場合に同様である。 On the other hand, if the label is “No”, the switching to the current operation mode or the timing of switching is not correct. Therefore, the coefficient, that is, the weight of each parameter in the evaluation value generation formula is recalculated (S504). When a bias value (that is, a constant) is added in the evaluation value calculation formula, the bias value is also included in the weight, and the weight multiplied by each parameter is collectively referred to as a weight vector. Here, the weight vector is changed by, for example, wi ← wi + Lρxi if the weight corresponding to the parameter xi is expressed as wi. Here, L is 1, and ρ is a small positive constant. ρ is a value that determines the step of change. If it is too small, the amount of calculation to reach an appropriate weight vector increases, and if it is too large, there is a possibility that excessive change will be performed. In general, ρ may be a different value for each parameter, or the sign may not match. Negative values are used for parameters whose weights are to be reduced by learning, and positive values are used for values that are desired to be increased. In this example, it is a positive value. In step S504, if there are a plurality of parameters used for evaluation value calculation, all the weights are recalculated. As a result, the weight is slightly increased and the recalculated evaluation value is increased. Therefore, in this example, the self-running mode is switched with a smaller inclination or a smaller acceleration by changing the weight. To do so, the driver is labeled “No” because the switch to self-propelled mode is too slow or the switch to driven mode is too early and feels free driving has been hindered This is because it is considered a case. Since this occurs when the evaluation value is too small with respect to the reference value, in this example, the weight is recalculated in the direction of increasing the evaluation value. This explanation is based on an example where the evaluation value is acceleration or vehicle body tilt, but the same applies when the evaluation value is based on other information.
 なおラベルが「否」の場合には、切り替えが遅すぎるのか早すぎるのかを運転者にラベルと共に入力させてもよい。その場合には、タイミングが遅すぎるなら(評価値が小さすぎるなら)ラベルLを1とし、早すぎる(評価値が大きすぎる)ならLを-1としてwiを再計算してもよい。 If the label is “No”, the driver may input whether the switching is too late or too early together with the label. In this case, if the timing is too late (if the evaluation value is too small), the label L may be set to 1, and if it is too early (the evaluation value is too large), L may be set to −1 and wi may be recalculated.
 新たな評価値の計算式が決まったなら、切り替え基準情報133に蓄積されたパラメータの先頭に着目する(S505)。そしてそこから順に、蓄積されたパラメータとステップS504で再計算した重みベクトルを用いて評価値を計算し、その評価値と基準値とから運転モードを決定する(S506)。そして決定した運転モードが正解であるか否かを判定する(S507)。着目したパラメータを用いて決定した運転モードと、そのパラメータに関連づけて記憶されている運転モードとが一致し、かつ対応するラベルが「良」である場合には正解である。また、着目したパラメータを用いて決定した運転モードと、そのパラメータに関連づけて記憶されている運転モードとが一致せず、かつ対応するラベルが「否」である場合も正解である。 When the calculation formula for the new evaluation value is determined, attention is paid to the head of the parameter stored in the switching reference information 133 (S505). Then, in order, the evaluation value is calculated using the accumulated parameters and the weight vector recalculated in step S504, and the operation mode is determined from the evaluation value and the reference value (S506). Then, it is determined whether or not the determined operation mode is correct (S507). A correct answer is obtained when the operation mode determined using the focused parameter matches the operation mode stored in association with the parameter and the corresponding label is “good”. It is also correct if the operation mode determined using the focused parameter does not match the operation mode stored in association with the parameter and the corresponding label is “No”.
 再計算した運転モードが正解であると判定されればステップS508に進み、着目パラメータが、切り替え基準情報133の最後のものか判定する(S508)。最後であれば、切り替え基準情報133に蓄積されたすべてのパラメータに対して運転者が求める条件で運転モードを切り替えることができたと判定できる。その場合には再計算した重みで元の重みを更新する(S510)。 If it is determined that the recalculated operation mode is correct, the process proceeds to step S508, and it is determined whether the parameter of interest is the last one of the switching reference information 133 (S508). If it is the last, it can be determined that the driving mode can be switched under the conditions required by the driver for all the parameters stored in the switching reference information 133. In that case, the original weight is updated with the recalculated weight (S510).
 一方、最後の項目でなければ次の項目に着目し(S509)、ステップS506から繰り返す。 On the other hand, if it is not the last item, pay attention to the next item (S509) and repeat from step S506.
 <本実施形態の効果>
 以上のように、自走車の加速度または傾きまたはそれら両方をパラメータとして運転モードを切り替えることで、たとえば自走する自走車11の運転を妨げになるような状況では自走モードで、そうでない状況では従動モードにすることで、自走車の運転の自由度を確保できる。他方では、追従車両の追従性が向上する。
<Effect of this embodiment>
As described above, by switching the driving mode using the acceleration and / or inclination of the self-propelled vehicle as a parameter, for example, in the situation that hinders the driving of the self-propelled self-propelled vehicle 11, the self-propelled mode is not. In the situation, the freedom mode of the self-propelled vehicle can be secured by setting the driven mode. On the other hand, the followability of the following vehicle is improved.
 さらに、従動モードでは追従車両の動力を利用しないために、電力や燃料の節約が可能となる。追従車両は大容量のバッテリや燃料タンクの搭載が困難であり、エネルギー源のチャージなしに走行可能な距離を伸ばすことができる。 Furthermore, since the power of the following vehicle is not used in the driven mode, power and fuel can be saved. It is difficult to mount a large-capacity battery or fuel tank on a follow-up vehicle, and the travelable distance can be extended without charging an energy source.
 また、運転モードの決定の条件を、上述した手順により機械学習することで、運転モードの切り替え条件を改善することができる。これにより、運転者の望む運転モードの切り替え条件を実現できる。また、クラウド等で提供される機械学習を用いれば、より高い機能を利用でき、またプログラムも容易となる。 In addition, the operation mode switching conditions can be improved by machine learning of the operation mode determination conditions according to the above-described procedure. Thereby, the switching condition of the driving mode desired by the driver can be realized. In addition, if machine learning provided in the cloud or the like is used, higher functions can be used and programs can be easily performed.
 なお、本例では、評価値を介した機械学習を行わせずに、自走車の傾きまたは加速度が所定の閾値を超えたなら運転モードを自走モードに、そうでなければ従動モードになるような単純な制御をしてもよい。これは、評価値として自走車の傾きまたは加速度そのものを採用し、図5の学習手順を行わないことで実現できる。ステップS403においては、走行状態情報である傾きや加速度を基準値と比較して、たとえば基準値を超えていれば運転モードを自走モードとするなどの決定をすることになる。 In this example, without performing machine learning via the evaluation value, the driving mode is set to the self-running mode if the inclination or acceleration of the self-propelling vehicle exceeds a predetermined threshold, and the driven mode is set otherwise. Such simple control may be performed. This can be realized by adopting the inclination or acceleration itself of the self-propelled vehicle as the evaluation value and not performing the learning procedure of FIG. In step S403, the inclination and acceleration, which are driving state information, are compared with a reference value, and if the reference value is exceeded, for example, the driving mode is determined to be the self-running mode.
 <第一実施形態のバリエーション1>
 さて、図4AのステップS401では走行状態情報として自走車から加速度および傾きまたはそのいずれかを取得し、取得した走行状態情報に基づいて評価値を算出している。以下では図6A~図6Dを参照して、他のパラメータから評価値を算出する例を説明する。
<Variation 1 of the first embodiment>
In step S401 in FIG. 4A, acceleration and / or inclination are acquired from the self-propelled vehicle as the driving state information, and an evaluation value is calculated based on the acquired driving state information. Hereinafter, an example in which an evaluation value is calculated from other parameters will be described with reference to FIGS. 6A to 6D.
 図6Aは、評価値算出のパラメータとして自車位置認識部102から取得した自車位置に基づいて運転モードを決定する際の手順を示す。ここでは自車位置に基づいて次のコーナー入口までの距離を特定し、それをパラメータとして評価位置を算出し、運転モードを決定する。具体的には、次のコーナー入口までの距離が閾値よりも小さければ自走モードを設定する。そのためにまず自車位置認識部102で特定した自車位置を取得する。次にその自車位置を地図情報132と照合する(S601)。そして地図上に置ける自車位置情報をパラメータとして、評価値を生成する(S602)。ここで特定される自車位置情報には、たとえば次のコーナー入口までの距離が含まれる。さらに直前のコーナー出口からの距離などが含まれてもよい。たとえば地図情報にコーナー入口や出口の位置が記憶されていれば、追従車両13は、自車の位置と進行方向とから地図上の次のカーブの入り口までの距離および/または出口からの距離を特定できる。その距離を、評価値を計算するためのパラメータとして利用する。 FIG. 6A shows a procedure for determining an operation mode based on the vehicle position acquired from the vehicle position recognition unit 102 as an evaluation value calculation parameter. Here, the distance to the next corner entrance is specified based on the own vehicle position, and the evaluation position is calculated using it as a parameter to determine the operation mode. Specifically, if the distance to the next corner entrance is smaller than the threshold value, the self-running mode is set. For this purpose, first, the vehicle position specified by the vehicle position recognition unit 102 is acquired. Next, the vehicle position is collated with the map information 132 (S601). Then, an evaluation value is generated using the vehicle position information that can be placed on the map as a parameter (S602). The vehicle position information specified here includes, for example, a distance to the next corner entrance. Further, the distance from the immediately preceding corner exit may be included. For example, if the position of the corner entrance or exit is stored in the map information, the following vehicle 13 determines the distance from the position of the own vehicle and the traveling direction to the entrance of the next curve on the map and / or the distance from the exit. Can be identified. The distance is used as a parameter for calculating the evaluation value.
 この場合、運転モードが従動モードから自走モードへと切り替わる際のラベルとして「否」が入力されると、そのタイミングを速くすべく評価値を大きくし、逆に運転モードが自走モードから従動モードへと切り替わる際のラベルとして「否」が入力されると、そのタイミングを遅くすべく評価値を小さくするよう学習が行われるのが望ましい。これは他のバリエーションや実施形態についても同様である。 In this case, if “No” is input as a label when the operation mode is switched from the driven mode to the self-propelled mode, the evaluation value is increased to speed up the timing, and conversely, the operation mode is switched from the self-propelled mode to the driven mode. When “No” is input as a label when switching to the mode, it is desirable to perform learning so as to reduce the evaluation value in order to delay the timing. The same applies to other variations and embodiments.
 このようにして、自車位置、特に次のコーナー入口までの距離に基づいても、運転モードを切り替えることもできる。コーナー入口までの距離に基づいて自走モードに切り替えることで、たとえばコーナー入口までの距離が近ければ自動モードに切り替えて、コーナー走行時の追従車両により運転の制限を軽減し、あるいは解消することができる。またコーナー通過後には従動モードに切り替えることで、追従車両の消費エネルギーを抑制することができる。 In this way, the operation mode can be switched based on the vehicle position, particularly the distance to the next corner entrance. By switching to the self-propelled mode based on the distance to the corner entrance, for example, if the distance to the corner entrance is short, the mode can be switched to the automatic mode, and the restriction of driving can be reduced or eliminated by the following vehicle during corner traveling it can. Moreover, the energy consumption of the following vehicle can be suppressed by switching to the driven mode after passing the corner.
 なお、本例で説明した評価値を介した機械学習を行わず、次のコーナーまでの距離が所定の閾値より小さいなら運転モードを自走モードに、そうでなければ従動モードになるように制御してもよい。そのために、図5の手順を実行せず、また評価値として次のコーナーまでの距離を用いればよい。 Note that the machine learning via the evaluation value described in this example is not performed, and the operation mode is controlled to the self-running mode if the distance to the next corner is smaller than the predetermined threshold, and the driven mode is set otherwise. May be. Therefore, the procedure of FIG. 5 is not executed, and the distance to the next corner may be used as the evaluation value.
 <第一実施形態のバリエーション2>
 図6Bは、評価値算出のパラメータとして制動の開始すなわちブレーキングポイントからの速度変化に基づいて運転モードを決定する際の手順を示す。具体的には、ブレーキングの開始からの速度変化が閾値を超えたなら自走モードを設定する。そのためにたとえばまず自走車11から、ブレーキングしたことを示す信号を受信する。そしてこの時点を基準として速度変化を特定する(S611)。特定した速度変化からステップS602と同じ要領で評価値を生成する。また、自走車11からの信号を受信せずに、たとえばカメラ40で取得した画像中のブレーキランプの点灯を認識し、その時点をブレーキングポイントとしても特定してもよい。
<Variation 2 of the first embodiment>
FIG. 6B shows a procedure for determining the operation mode based on the start of braking, that is, the speed change from the braking point, as an evaluation value calculation parameter. Specifically, the self-running mode is set when the speed change from the start of braking exceeds a threshold value. For this purpose, first, for example, a signal indicating that the vehicle has been braked is received from the self-propelled vehicle 11. Then, the speed change is specified based on this time (S611). An evaluation value is generated from the identified speed change in the same manner as in step S602. Further, without receiving a signal from the self-propelled vehicle 11, for example, the lighting of a brake lamp in an image acquired by the camera 40 may be recognized, and the time point may be specified as a braking point.
 なお、本例では、評価値を介した機械学習を行わず、速度変化が所定の閾値を超えたなら運転モードを自走モードに、そうでなければ従動モードになるように制御してもよい。そのために、図5の手順を実行せず、また評価値としてブレーキングからの速度変化そのものを用いればよい。 In this example, machine learning via the evaluation value is not performed, and the operation mode may be controlled to the self-running mode if the speed change exceeds a predetermined threshold value, and to the driven mode otherwise. . Therefore, the procedure of FIG. 5 is not executed, and the speed change itself from braking is used as the evaluation value.
 このようにして、制動を開始してからの速度変化に基づいて運転モードを切り替えることもできる。制動は多くの場合コーナー進入時にかけるので、この制御によりコーナー通過時は追従車両を自走モードに設定することができる。 In this way, the operation mode can be switched based on the speed change after the braking is started. Since braking is often applied when entering a corner, this control allows the following vehicle to be set to the self-propelled mode when passing the corner.
 <第一実施形態のバリエーション3>
 図6Cは、評価値算出のパラメータとして制動の開始すなわちブレーキングポイントからの経過時間に基づいて運転モードを決定する際の手順を示す。具体的には、ブレーキングの開始からの経過時間が閾値を超えたなら自走モードを設定する。そのためにたとえばまず自走車11から、ブレーキングしたことを示す信号を受信する。そしてこの時点を基準として経過時間を特定する(S621)。特定した経過時間からステップS602と同じ要領で評価値を生成する。ただし評価値は所定時間経過ごとに生成する。また、自走車11からの信号を受信せずに、たとえばカメラ40で取得した画像中のブレーキランプの点灯を認識し、その時点をブレーキングポイントとしても特定してもよい。
<Variation 3 of the first embodiment>
FIG. 6C shows a procedure for determining the operation mode based on the start of braking, that is, the elapsed time from the braking point, as an evaluation value calculation parameter. Specifically, when the elapsed time from the start of braking exceeds a threshold value, the self-running mode is set. For this purpose, first, for example, a signal indicating that the vehicle has been braked is received from the self-propelled vehicle 11. Then, the elapsed time is specified based on this time point (S621). An evaluation value is generated from the specified elapsed time in the same manner as in step S602. However, the evaluation value is generated every predetermined time. Further, without receiving a signal from the self-propelled vehicle 11, for example, the lighting of a brake lamp in an image acquired by the camera 40 may be recognized, and the time point may be specified as a braking point.
 なお、本例では、評価値を介した機械学習を行わず、経過時間が所定の閾値を超えたなら運転モードを自走モードに、そうでなければ従動モードになるように制御してもよい。そのために、図5の手順を実行せず、また評価値としてブレーキングからの経過時間そのものを用いればよい。 In this example, the machine learning via the evaluation value is not performed, and the operation mode may be controlled to the self-running mode if the elapsed time exceeds a predetermined threshold, and the driven mode may be controlled otherwise. . Therefore, the procedure shown in FIG. 5 is not executed, and the elapsed time from braking itself may be used as the evaluation value.
 このようにして、制動を開始してからの経過時間に基づいて運転モードを切り替えることもできる。制動は多くの場合コーナー進入時にかけるので、この制御によりコーナー通過時は追従車両を自走モードに設定することができる。 In this way, the operation mode can be switched based on the elapsed time from the start of braking. Since braking is often applied when entering a corner, this control allows the following vehicle to be set to the self-propelled mode when passing the corner.
 <第一実施形態のバリエーション4>
 図6Dは、評価値算出のパラメータとして自車状態認識部101や路面センサ50から取得した路面状態情報を利用する際の手順を示す。具体的には、路面状態の評価値としてたとえば摩擦係数が閾値を超えたなら自走モードを設定する。そのためにまず自車状態認識部101や路面センサ50で検知した路面の状態を取得する(S631)。次にその路面状態情報から評価値を生成する(S632)。路面状態情報には、路面の傾斜や摩擦係数などが含まれていてもよい。路面の傾斜はたとえば姿勢センサ60あるいは自車状態認識部101から自車の傾き情報を取得し、その傾きを路面の傾きとみなして用いてもよい。また摩擦係数は、その値そのものを取得するのは困難であるので、路面センサ50で撮影した路面の画像から、たとえば濡れや凹凸を検出し、それに基づいておおよその摩擦係数を推定してもよい。これはたとえば、摩擦係数のわかっている路面の画像パターンと路面センサ60で撮影した路面の画像とを比較し、一致または類似したパターンに予め関連付けられている摩擦係数を、現在の路面の摩擦係数として用いてもよい。なお用いるパラメータが変わるので、重みもまた異なるステップS401とは異なる値を用いてよい。
<Variation 4 of the first embodiment>
FIG. 6D shows a procedure when using road surface state information acquired from the vehicle state recognition unit 101 or the road surface sensor 50 as an evaluation value calculation parameter. Specifically, for example, if the friction coefficient exceeds a threshold value as the evaluation value of the road surface state, the self-running mode is set. For this purpose, first, the road surface state detected by the vehicle state recognition unit 101 or the road surface sensor 50 is acquired (S631). Next, an evaluation value is generated from the road surface state information (S632). The road surface state information may include a road surface inclination, a friction coefficient, and the like. For example, the inclination of the road surface may be obtained by acquiring inclination information of the own vehicle from the attitude sensor 60 or the own vehicle state recognition unit 101 and regarding the inclination as the inclination of the road surface. Further, since it is difficult to obtain the value of the friction coefficient itself, for example, wetting or unevenness may be detected from the road surface image taken by the road surface sensor 50, and the approximate friction coefficient may be estimated based on the detected wetness or unevenness. . For example, the road surface image pattern having a known friction coefficient is compared with the road surface image captured by the road surface sensor 60, and the friction coefficient previously associated with the matching or similar pattern is determined as the friction coefficient of the current road surface. It may be used as Since the parameter to be used is changed, the weight may be a value different from that in step S401.
 このようにして、路面状態に基づいても、運転モードを切り替えることもできる。路面状態に基づいて自走モードと従動モードとを切り替えることで、たとえば登坂路では自動モードに切り替えて、自走する自走車11の負担を軽減することができる。また、滑りやすい路面では、車輪に駆動力を与えることで一層滑りやすくなるので、従動モードに切り替えることで追従車両のスリップを起こしにくくことなどもできる。 In this way, the operation mode can be switched based on the road surface condition. By switching between the self-propelled mode and the driven mode based on the road surface state, for example, on an uphill road, it is possible to reduce the burden on the self-propelled vehicle 11 that switches to the automatic mode. Further, on a slippery road surface, it becomes more slippery by applying a driving force to the wheels. Therefore, it is possible to make the following vehicle less likely to slip by switching to the driven mode.
 なお、本例では、評価値を介した機械学習を行わず、路面の傾斜または摩擦係数が所定の閾値を超えたなら運転モードを自走モードに、そうでなければ従動モードになるように制御してもよい。そのために、図5の手順を実行せず、また評価値として路面状態を表す値を用いればよい。 In this example, machine learning via the evaluation value is not performed, and control is performed so that the driving mode is set to the self-running mode if the road slope or the friction coefficient exceeds a predetermined threshold, and the driven mode is set otherwise. May be. For this purpose, the procedure shown in FIG. 5 is not executed, and a value representing the road surface condition may be used as the evaluation value.
 <走行状態情報のバリエーション5>
 評価値の基準となるパラメータは、以上説明したものに限らず、他の値を用いてもよい。用いる値としては、追従車両で測定した、追従車両13自身の走行状態、自走車11で測定し、追従車両13に送信される自走車の走行状態、センサ等で取得される、走行している位置や地形、天候、時刻、道幅などの道路の状態、道路の混雑状況、心拍数や血圧などの運転者の生理情報、パッセンジャーの有無、自走車の型番、装着タイヤの種類など、様々なものを採用できる。またごく単純に、運転者の指示に応じて運転モードを切り替える構成とすることもできる。この場合には通信部11aを介して運転者の指示を追従車両13に伝達すると、指示に応じて運転モードが切り替えられる。
<Variation 5 of driving state information>
The parameter serving as a reference for the evaluation value is not limited to the parameter described above, and other values may be used. As the value to be used, the traveling state of the following vehicle 13 measured by the following vehicle, the traveling state of the traveling vehicle measured by the traveling vehicle 11 and transmitted to the following vehicle 13, acquired by a sensor, etc. The location, topography, weather, time, road width and other road conditions, road congestion, driver's physiological information such as heart rate and blood pressure, presence / absence of passengers, model number of self-propelled vehicle, type of tires, etc. Various things can be adopted. It is also possible to simply change the operation mode in accordance with the driver's instruction. In this case, when the driver's instruction is transmitted to the following vehicle 13 via the communication unit 11a, the driving mode is switched according to the instruction.
 また、評価値の算出に用いることができるパラメータとして、第一実施形態に記載した走行状態から、上述したものまで様々な情報を用いることができることを説明した。これらパラメータを別々に用いず、全てあるいは一部の情報から評価値を計算し、運転モードを切り替えてもよい。そのためには、評価値を、採用するパラメータそれぞれに重みを乗じた値の総和で求めてもよいし、あるいは、各バリエーションとして説明したパラメータから中間の評価値を計算し、その中間の評価値に重み付けをして最終的な評価値を計算する多層構造を採用してもよい。このようにすることで、より多くのパラメータに基づいて運転モードを決定することができ、よりきめ細かな状況に対応して運転者の要求する運転モードの切り替えタイミングを実現することができる。 Also, it has been explained that various information can be used from the running state described in the first embodiment to the above-described parameters as parameters that can be used for calculation of the evaluation value. Instead of using these parameters separately, the evaluation value may be calculated from all or part of the information, and the operation mode may be switched. For that purpose, the evaluation value may be obtained by the sum of values obtained by multiplying each of the adopted parameters by weight, or an intermediate evaluation value is calculated from the parameters described as each variation, and the intermediate evaluation value is calculated. A multilayer structure in which a final evaluation value is calculated by weighting may be adopted. By doing in this way, a driving mode can be determined based on more parameters, and the switching timing of the driving mode which a driver demands according to a more detailed situation can be realized.
 [第二実施形態]
 本実施形態では、上述した様々なパラメータのうち、自走車の状態に関する情報と、運転者に関する情報とを用いて運転モードを制御する例を説明する。
[Second Embodiment]
This embodiment demonstrates the example which controls a driving mode using the information regarding the state of a self-propelled vehicle among the various parameters mentioned above, and the information regarding a driver | operator.
 図7は、評価値算出のパラメータとして、走行状態情報と運転者の情報とを利用する際の手順を示す。まずカメラ40で取得した画像から、自走車の傾きおよび運転者(ライダー)の姿勢を含む走行状態情報を取得する(S701)。運転者の姿勢や車体の傾きは、たとえば画像中から特定した輪郭から軸を特定し、その軸の傾きから検出される。画像から自走車の走行状態を取得するためには、たとえば、傾きについてはカメラ40で撮影した画像から前走車のオブジェクトを認識し、その輪郭から上下の軸を特定することで、傾きを特定できる。追従車両13は本例では四輪車であり、傾かないことを前提とすれば、画像枠に対する傾きをそのまま自走車の傾きとして特定できる。また、運転者の姿勢も同様にして特定できる。 FIG. 7 shows a procedure when the driving state information and the driver information are used as the evaluation value calculation parameters. First, traveling state information including the inclination of the self-propelled vehicle and the posture of the driver (rider) is acquired from the image acquired by the camera 40 (S701). The driver's posture and the inclination of the vehicle body are detected, for example, by identifying the axis from the contour identified from the image and tilting the axis. In order to acquire the traveling state of the self-propelled vehicle from the image, for example, the inclination is recognized by recognizing the object of the preceding vehicle from the image taken by the camera 40 and specifying the upper and lower axes from the contour. Can be identified. In this example, the following vehicle 13 is a four-wheeled vehicle. If it is assumed that the following vehicle 13 is not inclined, the inclination with respect to the image frame can be directly specified as the inclination of the self-propelled vehicle. Further, the driver's posture can be specified in the same manner.
 次に自走車の走行状態を示す情報を、走行車から受信する(S702)。受信する情報には例えば、エンジン出力や選択されているギア、ブレーキの程度、加速度や各加速度などが含まれる。そのため本実施形態では、自走車にはそれら情報を検知するセンサが設けられている。なおエンジン出力そのものは測定が困難な場合もあるので、エンジン回転数で代えてもよい。またブレーキの程度は例えばブレークレバーやペダルの位置を示す情報で代えてもよい。 Next, information indicating the traveling state of the self-propelled vehicle is received from the traveling vehicle (S702). The received information includes, for example, engine output, selected gear, degree of braking, acceleration, each acceleration, and the like. Therefore, in this embodiment, the self-propelled vehicle is provided with a sensor that detects such information. Since the engine output itself may be difficult to measure, it may be replaced with the engine speed. The degree of braking may be replaced with information indicating the position of the break lever or pedal, for example.
 次に取得した情報をパラメータとして評価値を生成する(S703)。ステップS703では、取得した全てのパラメータに重み付けした総和を評価値としてもよいが、運転者に係る情報から算出した評価値と、自走車の走行状態に係る情報から算出した評価値とを算出し、それら評価値それぞれに重み付けした操作を最終的な評価値として算出してもよい。この評価値の算出過程が、運転者の状態と自走車の走行状態とから総合的に求められる車両-ライダーモデルを構成する。 Next, an evaluation value is generated using the acquired information as a parameter (S703). In step S703, the sum obtained by weighting all acquired parameters may be used as the evaluation value, but the evaluation value calculated from the information related to the driver and the evaluation value calculated from the information related to the traveling state of the self-propelled vehicle are calculated. Then, an operation weighted to each of the evaluation values may be calculated as a final evaluation value. This evaluation value calculation process constitutes a vehicle-rider model that is comprehensively obtained from the driver's state and the traveling state of the self-propelled vehicle.
 このようにして自走車の走行状態とその運転者の状態とを総合的に評価した車両-ライダーモデルを作成して運転モードを決定することができる。本例においては、図5の学習手順において、すべてのパラメータの重みを一様に重くせず、重みを大きくするパラメータを例えばランダムに選択するなどしてもよい。また前述したように、予め様々なパラメータ値の組み合わせとそれに対するラベルとを用意し、それらを教師データとしてたとえばクラウドサービスとして提供されている機械学習サービスを利用して学習させてもよい。そうすることで運転モードの切り替えをより高精度に行える。 In this way, it is possible to determine the driving mode by creating a vehicle-rider model that comprehensively evaluates the traveling state of the self-propelled vehicle and the state of the driver. In this example, in the learning procedure of FIG. 5, the weights of all the parameters may not be uniformly increased, and a parameter for increasing the weight may be selected at random. Also, as described above, various combinations of parameter values and labels for the parameter values may be prepared in advance and learned as teacher data using, for example, a machine learning service provided as a cloud service. By doing so, the operation mode can be switched with higher accuracy.
 [第三実施形態]
 第三の実施形態は追従車両13へのエネルギーの供給方式に関する。上記実施形態では、追従車両自身が電池や燃料といったエネルギー源を保持していた。本実施形態では、自走車から追従車両へとコードレス給電を行い、追従車両13を駆動させる。本実施形態では自走車と追従車両との間の距離は数メートル程度になると考えられるので、たとえば磁界共振方式やマイクロ波方式による送電などを採用する。磁界共振方式は共振器間の距離が短いほど効率が高いので、自走車と追従車両とに乗せる共振器は、たとえば前後に配置するのではなく、上下に重ねるように配置して、自走車と追従車両との距離が変化しても共振器間の距離が大きく変わらないように構成してもよい。このように構成することで共振器同士の衝突を防止することもできる。
[Third embodiment]
The third embodiment relates to a method for supplying energy to the following vehicle 13. In the above embodiment, the following vehicle itself holds an energy source such as a battery and fuel. In the present embodiment, cordless power feeding is performed from the self-propelled vehicle to the following vehicle, and the following vehicle 13 is driven. In this embodiment, since the distance between the self-propelled vehicle and the following vehicle is considered to be about several meters, for example, power transmission by a magnetic field resonance method or a microwave method is adopted. Since the magnetic field resonance method has a higher efficiency as the distance between the resonators is shorter, the resonators to be mounted on the self-propelled vehicle and the following vehicle, for example, are not arranged in front and back, but are arranged so as to overlap each other. You may comprise so that the distance between resonators may not change greatly even if the distance of a vehicle and a following vehicle changes. By configuring in this way, collision between resonators can also be prevented.
 本実施形態によれば、追従車両の重量増につながる電池や燃料を積載せずに済み、重量を軽減できる。また自走車から給電を受けられる限り追従車両は自走できる。 According to the present embodiment, it is not necessary to load batteries and fuel that lead to an increase in the weight of the following vehicle, and the weight can be reduced. In addition, the following vehicle can be self-propelled as long as it can receive power from the self-propelled vehicle.
 [第四実施形態]
 第四の実施形態では、追従車両13の積載部の構成を目的に応じて様々にすることができる。たとえば貨物用や宿泊用、ペットの運搬用などの目的に応じて様々な構成とする。また、図1に示した積載部のみを交換可能に構成して、ひとつの追従車両を多目的に使用することもできる。
[Fourth embodiment]
In 4th embodiment, the structure of the loading part of the tracking vehicle 13 can be varied according to the objective. For example, various configurations are used according to purposes such as cargo, accommodation, and pet transportation. Further, only the loading unit shown in FIG. 1 can be replaced, and one following vehicle can be used for multiple purposes.
 この構成により、ユーザの選択の余地が広がり、様々な用途に追従車両を使用することができる。 This configuration increases the user's choice and allows the vehicle to be used for various purposes.
 [実施形態のまとめ]
 本実施形態に係る発明は以下のようにまとめることができる。
[Summary of Embodiment]
The invention according to this embodiment can be summarized as follows.
 その第一の側面は以下のようなものである。 The first aspect is as follows.
 自走車(11)と共に走行する追従車両(13)であって、
 動力により自律的に走行するための自走手段(72)と、
 走行状態情報を取得する取得手段(50,60,101,102,103)と、
 前記自走車にけん引されて走行する従動モードと、前記自走手段(72)により自律的に走行する自走モードの何れかのモードで走行する走行制御手段(112)と、を有し、
 前記走行制御手段(112)は、取得した前記走行状態情報に基づいて、前記従動モードと前記自走モードとを切り替える、追従車両。
A follower vehicle (13) traveling with a self-propelled vehicle (11),
Self-propelled means (72) for traveling autonomously by power;
Acquisition means (50, 60, 101, 102, 103) for acquiring running state information;
A travel control means (112) that travels in any mode of a driven mode that is towed by the self-propelled vehicle and travels autonomously by the self-propelled means (72);
The traveling vehicle (112) is a following vehicle that switches between the driven mode and the self-running mode based on the acquired traveling state information.
 この構成により、自走車の走行状態により自動的にモードが切り替わることにより、自走車を自在に操作したいときには、自走モードとなり、従動車を牽引していてもツーリングの快適性を損なわない。 With this configuration, the mode is automatically switched according to the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, it becomes the self-propelled mode and does not impair the touring comfort even if the driven vehicle is towed. .
 またその第二の側面は以下のようなものである。 The second aspect is as follows.
 上記追従車両であって、
 通信手段(65)をさらに有し、
 前記取得手段(103)は、前記走行状態情報として前記自走車の走行状態情報を前記通信手段(65)を介して前記自走車から取得する、追従車両。
The following vehicle,
A communication means (65);
The follow-up vehicle, wherein the acquisition means (103) acquires the traveling state information of the self-propelled vehicle as the traveling state information from the self-propelled vehicle via the communication means (65).
 この構成により、追従車両は自走車の走行状態を検知するための構成を持つ必要がなく、構成を簡素にできる。 With this configuration, the following vehicle need not have a configuration for detecting the traveling state of the self-propelled vehicle, and the configuration can be simplified.
 またその第三の側面は以下のようなものである。 The third aspect is as follows.
 上記追従車両であって、
 前記取得手段は路面状態を検知する路面状態検知手段(50)を含み、前記走行状態情報として前記路面状態を取得する、追従車両。
The following vehicle,
The following vehicle includes a road surface state detection unit (50) for detecting a road surface state, and acquires the road surface state as the traveling state information.
 この構成により、路面状態によってモードが自動的に切り替わることで、牽引している従動車に注意を払うことなく単独で自走車を運転している感覚で走行することができる。 With this configuration, the mode is automatically switched depending on the road surface condition, so that it is possible to travel as if driving a self-propelled vehicle alone without paying attention to the driven vehicle being towed.
 またその第四の側面は以下のようなものである。 The fourth aspect is as follows.
 上記追従車両であって、
 位置情報を検知する位置検知手段(102)と、
 地図情報を記憶した地図記憶手段(132)と、をさらに有し、
 前記取得手段は、前記地図情報が示す地図上の位置を前記走行状態として取得する、追従車両。
The following vehicle,
Position detecting means (102) for detecting position information;
Map storage means (132) storing map information;
The follow-up vehicle, wherein the acquisition unit acquires a position on a map indicated by the map information as the traveling state.
 この構成によれば、カーブなどで、自走車の対応が遅れたときでも安全に旋回することができる。 According to this configuration, it is possible to turn safely even when the response of the self-propelled vehicle is delayed due to a curve or the like.
 またその第五の側面は以下のようなものである。 The fifth aspect is as follows.
 上記追従車両であって、
 前記自走車は二輪車(11)であり、
 前記二輪車および該二輪車に乗車しているライダーを撮影して画像データを取得する撮影手段(40)と、
 前記撮影手段(40)により撮影された画像データに基づいて前記自走車の傾きと前記ライダーの姿勢とを示す姿勢情報を取得する手段(112、S702)と、をさらに有し、
 前記取得手段は、前記姿勢情報を前記走行状態情報として取得する、追従車両。
The following vehicle,
The self-propelled vehicle is a motorcycle (11),
Photographing means (40) for photographing the two-wheeled vehicle and a rider riding on the two-wheeled vehicle to obtain image data;
Means (112, S702) for obtaining posture information indicating the inclination of the self-propelled vehicle and the posture of the rider based on the image data photographed by the photographing means (40);
The follow-up vehicle, wherein the acquisition means acquires the posture information as the traveling state information.
 この構成により、自走車から情報を取得することなく運転モードを制御できるため、自走車の構成を簡素にできる。 This configuration allows the driving mode to be controlled without acquiring information from the self-propelled vehicle, thereby simplifying the configuration of the self-propelled vehicle.
 またその第六の側面は以下のようなものである。 The sixth aspect is as follows.
 上記追従車両であって、
 通信手段(65)をさらに有し、
 前記走行制御手段(112)はさらに、前記自走車からの指示を前記通信手段(65)により受信し、前記指示に基づいて、前記従動モードと前記自走モードとを切り替える、追従車両。
The following vehicle,
A communication means (65);
The travel control means (112) further receives an instruction from the self-propelled vehicle by the communication means (65), and switches between the driven mode and the self-propelled mode based on the instruction.
 この構成により、運転モードを切り替えるための制御が不要となり、より構成を簡素にできる。 This configuration eliminates the need for control for switching the operation mode, thereby further simplifying the configuration.
 またその第七の側面は以下のようなものである。 The seventh aspect is as follows.
 上記追従車両であって、
 前記走行制御手段により前記従動モードと前記自走モードとを切り替えた際の走行状態情報と、該走行状態情報に対応した運転モードとを記憶する記憶手段(133)と、
 前記運転モードの切り替えの良否を良否信号として入力し、前記走行状態情報および前記運転モードと関連付けて前記記憶手段によりさらに記憶させるための入力手段(11a)と、
 前記良否信号と、対応する前記走行状態情報とに基づいて、前記従動モードと前記自走モードとを切り替えるタイミングを修正する学習手段(140)と
をさらに有する追従車両。
The following vehicle,
Storage means (133) for storing the running state information when the driven mode and the self-running mode are switched by the running control means, and the driving mode corresponding to the running state information;
Input means (11a) for inputting the pass / fail of switching of the operation mode as a pass / fail signal, and further storing the storage state information and the operation mode in association with the storage means;
A follow-up vehicle further comprising learning means (140) for correcting timing for switching between the driven mode and the self-running mode based on the pass / fail signal and the corresponding running state information.
 この構成により、学習機能で運転者の望むタイミングで運転モードの切り替えが可能となる。 This configuration enables the operation mode to be switched at the timing desired by the driver with the learning function.
 またその第八の側面は以下のようなものである。 The eighth aspect is as follows.
 上記追従車両であって、
 前記自走車を認識する認識手段(103)をさらに有し、
 前記走行制御手段は、前記自走モードでは前記認識手段により認識した前記自走車を追尾するように走行する、追従車両。
The following vehicle,
Recognizing means (103) for recognizing the self-propelled vehicle;
In the self-propelled mode, the travel control means travels so as to track the self-propelled vehicle recognized by the recognition means.
 この構成により、追従車両は自走車を追尾できる。 This configuration allows the following vehicle to track a self-propelled vehicle.
 またその第九の側面は以下のようなものである。 The ninth aspect is as follows.
 自走車(101)と、自走車(101)と共に走行する追従車両(103)とを含む車両システムであって、
 前記追従車両は、
 動力により自律的に走行するための自走手段(72)と、
 走行状態情報を取得する取得手段(50,60,65,101,102)と、
 前記自走車にけん引されて走行する従動モードと、前記自走手段(72)により自律的に走行する自走モードの何れかの運転モードで走行する走行制御手段(112)と、
 前記モードの指示を受信する通信手段(65)とを有し、
 前記自走車(101)は、
 取得した前記走行状態情報に基づいて、運転モードを、前記従動モードと前記自走モードとで切り替える決定手段と、
 前記運転モードを前記追従車両に送信する通信手段(11a)と
を有する車両システム。
A vehicle system including a self-propelled vehicle (101) and a following vehicle (103) that travels with the self-propelled vehicle (101),
The following vehicle is
Self-propelled means (72) for traveling autonomously by power;
Acquisition means (50, 60, 65, 101, 102) for acquiring running state information;
Travel control means (112) that travels in one of the following modes: a driven mode that is towed by the self-propelled vehicle; and a self-propelled mode that travels autonomously by the self-propelled means (72);
Communication means (65) for receiving an instruction of the mode,
The self-propelled vehicle (101)
Determination means for switching the operation mode between the driven mode and the self-running mode based on the acquired driving state information;
The vehicle system which has a communication means (11a) which transmits the said driving mode to the said following vehicle.
 この構成により、自走車の走行状態により自動的にモードが切り替わることにより、自走車を自在に操作したいときには、自走モードとなり、従動車を牽引していてもツーリングの快適性を損なわない。さらに、モードの決定を自走車が行うことで、追従車両の構成を簡単化できる。 With this configuration, the mode is automatically switched according to the traveling state of the self-propelled vehicle, so that when the self-propelled vehicle is to be operated freely, it becomes the self-propelled mode and does not impair the touring comfort even if the driven vehicle is towed. . Furthermore, since the self-propelled vehicle determines the mode, the configuration of the following vehicle can be simplified.
 またその第十の側面は以下のようなものである。 The tenth aspect is as follows.
 上記追従車両であって、
 前記走行状態には、前記追従車両の重量、エンジン出力、速度、加速度、前記自動車が二輪車の場合にはその傾斜、コーナー入口までの距離を含む、追従車両。
The following vehicle,
The following vehicle includes a weight, an engine output, a speed, an acceleration of the following vehicle, a slope when the automobile is a two-wheeled vehicle, and a distance to a corner entrance in the traveling state.
 この構成により様々なパラメータにより運転モードを決定でき、きめ細かな制御が可能となる。 This configuration makes it possible to determine the operation mode with various parameters and to perform fine control.
 またその第十一の側面は以下のようなものである。 The eleventh aspect is as follows.
 上記追従車両であって、
 前記走行制御手段は、自走モードであるか従動モードであるかに関わらず、前記自走車の制動を検知し、前記自走車の制動を検知した場合には、制動をかける、追従車両。
The following vehicle,
The traveling control means detects braking of the self-propelled vehicle regardless of whether it is in the self-propelled mode or the driven mode, and applies braking when detecting the braking of the self-propelled vehicle. .
 この構成により自走車への追突を防止できる。 This configuration can prevent a rear-end collision with a self-propelled vehicle.
 またその第十二の側面は以下のようなものである。 The twelfth aspect is as follows.
 上記追従車両であって、
 前記自走手段による自律走行を、電力をエネルギー源として行い、
 前記追従車両はさらに、前記自走車からコードレスで電力の供給を受けるコードレス受電手段をさらに有する、追従車両。
The following vehicle,
Autonomous traveling by the self-propelled means is performed using electric power as an energy source,
The following vehicle further includes cordless power receiving means that receives cordless power supply from the self-propelled vehicle.
 この構成により、追従車両の軽量化が実現でき、また自走モードでの走行距離を伸ばすことができる。 This configuration makes it possible to reduce the weight of the following vehicle and to increase the distance traveled in the self-running mode.
 またその第十三の側面は以下のようなものである。 The thirteenth aspect is as follows.
 上記追従車両であって、
 積載物を搭載する、交換可能な積載手段をさらに有する、追従車両。
The following vehicle,
A follow-up vehicle further comprising an exchangeable loading means for loading a load.
 この構成により、ユーザの所望する積載手段を利用することができる。 This configuration makes it possible to use the loading means desired by the user.
 本発明は上記実施の形態に制限されるものではなく、本発明の精神及び範囲から離脱することなく、様々な変更及び変形が可能である。従って、本発明の範囲を公にするために、以下の請求項を添付する。 The present invention is not limited to the above embodiment, and various changes and modifications can be made without departing from the spirit and scope of the present invention. Therefore, in order to make the scope of the present invention public, the following claims are attached.
1 運転制御システム、11自走車、12 けん引索、13 追従車両、100 制御部、112 走行制御部、1121 運転モード決定部、1122 運転モード、140 学習制御部 1 driving control system, 11 self-propelled vehicle, 12 towing, 13 following vehicle, 100 control unit, 112 driving control unit, 1121 driving mode determining unit, 1122 driving mode, 140 learning control unit

Claims (9)

  1.  自走車(11)と共に走行する追従車両(13)であって、
     動力により自律的に走行するための自走手段(72)と、
     走行状態情報を取得する取得手段(50,60,101,102,103)と、
     前記自走車(11)にけん引されて走行する従動モードと、前記自走手段(72)により自律的に走行する自走モードの何れかのモードで走行する走行制御手段(112)と、を有し、
     前記走行制御手段(112)は、取得した前記走行状態情報に基づいて、前記従動モードと前記自走モードとを切り替える、追従車両。
    A follower vehicle (13) traveling with a self-propelled vehicle (11),
    Self-propelled means (72) for traveling autonomously by power;
    Acquisition means (50, 60, 101, 102, 103) for acquiring running state information;
    A travel control means (112) that travels in one of a driven mode that is towed by the self-propelled vehicle (11) and a self-propelled mode that travels autonomously by the self-propelled means (72); Have
    The traveling vehicle (112) is a following vehicle that switches between the driven mode and the self-running mode based on the acquired traveling state information.
  2.  請求項1に記載の追従車両であって、
     通信手段(65)をさらに有し、
     前記取得手段(103)は、前記走行状態情報として前記自走車の走行状態情報を前記通信手段(65)を介して前記自走車から取得する、追従車両。
    The following vehicle according to claim 1,
    A communication means (65);
    The follow-up vehicle, wherein the acquisition means (103) acquires the traveling state information of the self-propelled vehicle as the traveling state information from the self-propelled vehicle via the communication means (65).
  3.  請求項1に記載の追従車両であって、
     前記取得手段は路面状態を検知する路面状態検知手段(50)を含み、前記走行状態情報として前記路面状態を取得する、追従車両。
    The following vehicle according to claim 1,
    The following vehicle includes a road surface state detection unit (50) for detecting a road surface state, and acquires the road surface state as the traveling state information.
  4.  請求項1に記載の追従車両であって、
     位置情報を検知する位置検知手段(102)と、
     地図情報を記憶した地図記憶手段(132)と、をさらに有し、
     前記取得手段は、前記地図情報が示す地図上の位置を前記走行状態として取得する、追従車両。
    The following vehicle according to claim 1,
    Position detecting means (102) for detecting position information;
    Map storage means (132) storing map information;
    The follow-up vehicle, wherein the acquisition unit acquires a position on a map indicated by the map information as the traveling state.
  5.  請求項1に記載の追従車両であって、
     前記自走車は二輪車(11)であり、
     前記二輪車および該二輪車に乗車しているライダーを撮影して画像データを取得する撮影手段(40)と、
     前記撮影手段(40)により撮影された画像データに基づいて前記自走車の傾きと前記ライダーの姿勢とを示す姿勢情報を取得する手段(112、S702)と、をさらに有し、
     前記取得手段は、前記姿勢情報を前記走行状態情報として取得する、追従車両。
    The following vehicle according to claim 1,
    The self-propelled vehicle is a motorcycle (11),
    Photographing means (40) for photographing the two-wheeled vehicle and a rider riding on the two-wheeled vehicle to obtain image data;
    Means (112, S702) for obtaining posture information indicating the inclination of the self-propelled vehicle and the posture of the rider based on the image data photographed by the photographing means (40);
    The follow-up vehicle, wherein the acquisition means acquires the posture information as the traveling state information.
  6.  請求項1に記載の追従車両であって、
     通信手段(65)をさらに有し、
     前記走行制御手段(112)はさらに、前記自走車からの指示を前記通信手段(65)により受信し、前記指示に基づいて、前記従動モードと前記自走モードとを切り替える、追従車両。
    The following vehicle according to claim 1,
    A communication means (65);
    The travel control means (112) further receives an instruction from the self-propelled vehicle by the communication means (65), and switches between the driven mode and the self-propelled mode based on the instruction.
  7.  請求項1乃至5のいずれか一項に記載の追従車両であって、
     前記走行制御手段により前記従動モードと前記自走モードとを切り替えた際の走行状態情報と、該走行状態情報に対応した運転モードとを記憶する記憶手段(133)と、
     前記運転モードの切り替えの良否を良否信号として入力し、前記走行状態情報および前記運転モードと関連付けて前記記憶手段によりさらに記憶させるための入力手段(11a)と、
     前記良否信号と、対応する前記走行状態情報とに基づいて、前記従動モードと前記自走モードとを切り替えるタイミングを修正する学習手段(140)と
    をさらに有する追従車両。
    A follower vehicle according to any one of claims 1 to 5,
    Storage means (133) for storing the running state information when the driven mode and the self-running mode are switched by the running control means, and the driving mode corresponding to the running state information;
    Input means (11a) for inputting the pass / fail of switching of the operation mode as a pass / fail signal, and further storing the storage state information and the operation mode in association with the storage means;
    A follow-up vehicle further comprising learning means (140) for correcting timing for switching between the driven mode and the self-running mode based on the pass / fail signal and the corresponding running state information.
  8.  請求項1乃至7のいずれか一項に記載の追従車両であって、
     前記自走車を認識する認識手段(103)をさらに有し、
     前記走行制御手段(112)は、前記自走モードでは前記認識手段により認識した前記自走車を追尾するように走行する、追従車両。
    A follower vehicle according to any one of claims 1 to 7,
    Recognizing means (103) for recognizing the self-propelled vehicle;
    The travel control means (112) is a following vehicle that travels so as to track the self-propelled vehicle recognized by the recognition means in the self-propelled mode.
  9.  自走車(101)と、自走車(101)と共に走行する追従車両(13)とを含む車両システムであって、
     前記追従車両は、
     動力により自律的に走行するための自走手段(72)と、
     走行状態情報を取得する取得手段(50,60,65,101,102)と、
     前記自走車にけん引されて走行する従動モードと、前記自走手段(72)により自律的に走行する自走モードの何れかの運転モードで走行する走行制御手段(112)と、
     前記モードの指示を受信する通信手段(65)とを有し、
     前記自走車(101)は、
     取得した前記走行状態情報に基づいて、運転モードを、前記従動モードと前記自走モードとで切り替える決定手段と、
     前記運転モードを前記追従車両に送信する通信手段(11a)と
    を有する車両システム。
    A vehicle system including a self-propelled vehicle (101) and a following vehicle (13) that travels with the self-propelled vehicle (101),
    The following vehicle is
    Self-propelled means (72) for traveling autonomously by power;
    Acquisition means (50, 60, 65, 101, 102) for acquiring running state information;
    Travel control means (112) that travels in one of the following modes: a driven mode that is towed by the self-propelled vehicle; and a self-propelled mode that travels autonomously by the self-propelled means (72);
    Communication means (65) for receiving an instruction of the mode,
    The self-propelled vehicle (101)
    Determination means for switching the operation mode between the driven mode and the self-running mode based on the acquired driving state information;
    The vehicle system which has a communication means (11a) which transmits the said driving mode to the said following vehicle.
PCT/JP2017/013620 2017-03-31 2017-03-31 Trailer WO2018179345A1 (en)

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