REMOTE CONTROL DEVICE

A remote control device is a remote control device configured to control one or more mobile objects via a network, which includes a receiver configured to receive mobile object information including a first state quantity of a state quantity of the mobile object and surrounding information around the mobile object, a trajectory generation unit configured to generate a target trajectory of the mobile object on the basis of the surrounding information, a mobile object estimation unit configured to estimate transmission latency of the network, a gain setting unit configured to set a control gain on the basis of the transmission latency, a control amount calculation unit configured to calculate a control amount for causing the mobile object to follow the target trajectory on the basis of the mobile object information and the control gain, and a transmitter configured to transmit the control amount to the mobile object.

TECHNICAL FIELD

The present disclosure relates to a remote control device for controlling one or more mobile objects via a network.

BACKGROUND ART

In recent years, progress has been made in the development of remote control devices that implement autonomous operation such as autonomous valet parking and autonomous transportation by transmitting/receiving data to and from a mobile object located at a remote location. A network constructed by wireless communication is used for data transmission/reception. In a case where the network is adopted, the distance between the remote control device and the mobile object, obstacles therebetween, and the like, cause transmission latency in transmitting/receiving data. If the control of the mobile object is to be made under such an environment, the mobile object may fall into an unstable state.

Patent Document 1 discloses a travel control method and a travel control device for autonomously operated vehicles in which the effect of transmission latency is to be reduced by controlling a plurality of vehicles in focus.

PRIOR ART DOCUMENTS

SUMMARY

Problem to be Solved by the Invention

In Patent Document 1, traveling priorities are determined for a plurality of vehicles determined to have entered an intersection, and the vehicles are controlled on the basis of the traveling priorities. However, due to the traveling priorities being determined after entering the intersection, a vehicle with a low traveling priority is requested to stop immediately. For this reason, smooth traveling of the vehicles may fail to implement.

The present disclosure has been made to solve the above-described problem, and an object of the present disclosure is to provide a remote control device that implements smooth traveling of a mobile object.

Means to Solve the Problem

According to the present disclosure, a remote control device configured to control one or more mobile objects via a network, includes a receiver configured to receive mobile object information including a first state quantity of a state quantity of the mobile object and surrounding information regarding the surrounding of the mobile object, a trajectory generation unit configured to generate a target trajectory of the mobile object on the basis of the surrounding information, a mobile object estimation unit configured to estimate transmission latency of the network, a gain setting unit configured to set a control gain on the basis of the transmission latency, a control amount calculation unit configured to calculate a control amount for causing the mobile object to follow the target trajectory on the basis of the mobile object information and the control gain, and a transmitter configured to transmit the control amount to the mobile object.

Effects of the Invention

According to the present disclosure, smooth traveling can be implemented since the remote control device generates the target trajectory of the mobile object on the basis of the surrounding information around the mobile object, and controls the mobile object to follow the target trajectory.

DESCRIPTION OF EMBODIMENT(S)

FIG.1is a block diagram illustrating an example of a configuration of a remote control device6when controlling one mobile object2in the present embodiment.FIG.1is a block diagram illustrating a configuration including a network1, a mobile object2, an object information acquisition unit4, an environment information acquisition unit5, a remote control device6, and a map database7.FIG.1is a block diagram of the remote control device6that controls one mobile object2(first mobile object21) via a network1.

The network1is capable of transmitting/receiving data with a plurality of components being mutually connected with cables, radio waves, and the like. The network includes various methods such as a local area network (LAN), a wide area network (WAN), Internet, telephone lines, and wireless communication. In the present disclosure, the network is not limited thereto, and any medium can be adoptable as long as data can be transmitted/received between the remote control device6and the mobile object2located at a remote location.

The mobile object2is the first mobile object21. The first mobile object21travels on the basis of the control amount from a transmitter65of the remote control device6. The configuration of the first mobile object21will be described later in detail with reference toFIG.5.

The object information acquisition unit4is configured with one or more sensors installed around the mobile object2. The object information acquisition unit4acquires the positions and speeds of obstacles such as other vehicles, bicycles, and pedestrians around the mobile object2as surrounding information. Also, the object information acquisition unit4can acquire the position and speed of the mobile object2per se as mobile object information. When the mobile object2is provided with an internal sensor2b, the mobile object information can also be obtained from the internal sensor2b. The object information acquisition unit4transmits the mobile object information and the surrounding information to the receiver62in the remote control device6via the network1. It should be noted that the object information acquisition unit4includes a clock synchronization unit41. The clock synchronization unit41has a function to synchronize the timing of data transmission/reception in cooperation with a clock synchronization unit2ain the mobile object2, a clock synchronization unit51in the environment information acquisition unit5, and a clock synchronization unit61in the remote control device6.

As with the object information acquisition unit4, the environment information acquisition unit5is configured with one or more sensors installed at a remote location. The environment information acquisition unit5acquires environment information such as traffic lights and stop lines. The environment information acquisition unit5transmits the environment information to the receiver62in the remote control device6via the network1. The environment information may be included in the surrounding information acquired by the object information acquisition unit4. Hereinafter, the environmental information is assumed to be included in the surrounding information, and the surrounding information is to be used as a unified term thereof. Also, the sensor used in the environment information acquisition unit5may be installed on the mobile object2per se. It should be noted that the environment information acquisition unit5includes the clock synchronization unit51. The clock synchronization unit51has a function to synchronize the timing of data transmission/reception in cooperation with the clock synchronization unit2a, a clock synchronization unit41, and a clock synchronization unit61.

The sensors used in the object information acquisition unit4and the environment information acquisition unit5are, for example, cameras, Light Detection and Ranging (LiDAR), and radar.

The camera acquires surrounding images and outputs the images as image data.

LiDAR detects the positions of objects by irradiating laser beams to the surrounding area and detecting the time difference of the laser beams reflecting off a surrounding object and coming back.

The radar measures the relative distance and relative speed of obstacles existing in the surroundings with respect to the radar by irradiating toward the surroundings and detecting the reflected waves thereof, and outputs the measurement results.

In a case where the Global Navigation Satellite System (GNSS) sensor, which detects the absolute positions of obstacles and the like around mobile object2, is installed on obstacles such as the mobile object2or other vehicles, and the GNSS sensor can transmit absolute position information to the remote control device6via the network1, the object information acquisition unit4is unnecessary since object information can be detected by the GNSS sensor.

The map database7stores map data around the mobile object2. Although the trajectory generation unit63is connected to the map database7inFIG.1, not only the trajectory generation unit63but also each component in the remote control device6can access the map database7. When the mobile object2is a vehicle, the map database7includes data related to traveling in many cases such as road center coordinate information, stop line information, white line information, and traveling possible areas. The remote control device6includes the clock synchronization unit61, the receiver62, the trajectory generation unit63, a mobile object control calculation unit64, and the transmitter65.

The clock synchronization unit61has a function to synchronize the timing of data transmission/reception in cooperation with the clock synchronization unit2a, a clock synchronization unit41, and a clock synchronization unit51.

The receiver62receives the mobile object information and the surrounding information from the object information acquisition unit4, the surrounding information from the environment information acquisition unit5, and the mobile object information from the mobile object2. The mobile object information is composed of a first state quantity such as the position and speed of the mobile object2. That is, the first state quantity represents the state quantity acquired by the sensor. The receiver62receives the mobile object information including the first state quantity of the state quantity of the mobile object2and the surrounding information around the mobile object2.

The trajectory generation unit63generates a target trajectory of the mobile object2on the basis of the map data from the map database7and the surrounding information from the receiver62. Here, the target trajectory is a combination of a target route and a target speed. Alternatively, the target trajectory may be, for example, a combination of a target route and a target position. Also, the target trajectory is not limited to the target speed or the target position, and any may be adoptable as long as it is a state quantity of the mobile object2. Note that the trajectory generation unit63may generate the target trajectory of the mobile object2on the basis of the surrounding information alone. The method by which the trajectory generation unit63generates the target trajectory will be described later in detail with reference toFIGS.7and8.

The mobile object control calculation unit64includes a first mobile object control calculation unit641. On the basis of the mobile object information from the receiver62and the target trajectory from the trajectory generation unit63, the first mobile object control calculation unit641calculates a control amount for causing the first mobile object21to follow the target trajectory. When the mobile object2is a vehicle, the control amount is, for example, a target steering amount and a target acceleration/deceleration amount. The first mobile object control calculation unit641will be described later in detail with reference toFIG.3.

The transmitter65transmits the control amount from the first mobile object control calculation unit641to the first mobile object21via the network1.

FIG.2is a block diagram illustrating an example of a configuration of the remote control device6when controlling two or more mobile objects2in the present embodiment.FIG.2is different fromFIG.1in terms of the mobile object2being the first mobile object21, the second mobile object22, and the like, and the mobile object control calculation unit64including the first mobile object control calculation unit641and the second mobile object control calculation unit642and the like. The description is omitted since the configuration is the same asFIG.1except for these elements.

The receiver62receives the mobile object information and the surrounding information from the object information acquisition unit4, the surrounding information from the environment information acquisition unit5, and the mobile object information from the respective mobile objects2

The trajectory generation unit63generates each target trajectory for two or more mobile objects2on the basis of the map data from the map database7and the surrounding information from the receiver62. The method by which the trajectory generation unit63generates each target trajectory for two or more mobile objects2will be described later in detail with reference toFIGS.9and10.

Of the mobile object control calculation unit64, the first mobile object control calculation unit641calculates a control amount for the first mobile object21on the basis of the mobile object information of the first mobile object21and the target trajectory of the first mobile object21. Similarly, the second mobile object control calculation unit642calculates a control amount for the second mobile object22on the basis of the mobile object information of the second mobile object22and the target trajectory of the second mobile object22. In a case where the number of mobile objects2is three or more, the mobile object control calculation unit64additionally includes a third mobile object control calculation unit or the like in accordance with an increase in the number of mobile objects2.

The transmitter65transmits the control amount from the first mobile object control calculation unit641and the control amount from the second mobile object control calculation unit642and the like to the mobile objects2via the network1. The control amount from the first mobile object control calculation unit641is transmitted to the first mobile object21. Similarly, the control amount from the second mobile object control calculation unit642is transmitted to the second mobile object22.

FIG.3is a block diagram illustrating an example of a configuration of the first mobile object control calculation unit641according to the present embodiment. The first mobile object control calculation unit641includes a mobile object estimation unit64a, a gain setting unit64b, a control amount calculation unit64c, and a control implementability determination unit64d. In the case where the remote control device6remotely controls two or more mobile objects2, the second mobile object control calculation unit642and the like similarly includes a mobile object estimation unit64a, a gain setting unit64b, a control amount calculation unit64c, and a control implementability determination unit64d.

The mobile object estimation unit64aestimates the transmission latency of the network1. However, the mobile object estimation unit64amay estimate the distribution of the transmission latency of the network1since the transmission latency of the network1can fluctuate. The distribution indicates, for example, a probability distribution, however, it is not limited to a probability distribution. The mobile object estimation unit64amay estimate the distribution of the transmission latency on the basis of the transmission latency previously acquired before the remote control device6remotely controls the mobile object2, or may estimate the distribution of the transmission latency online while remotely controlling the mobile object2. Further, the mobile object estimation unit64amay estimate the distribution of coefficients for the state quantity of the mobile object2on the basis of the mobile object information from the receiver62. The coefficients are the mass of the mobile object2and the moment of inertia. In particular, when the mobile object2is a vehicle, cornering stiffness and the like are also included. As with the transmission latency of the network1, these coefficients also affect control stability and can fluctuate. The coefficients are estimated on the basis of a state equation and the state quantity regarding to the mobile object2.

The gain setting unit64bsets a control gain on the basis of the transmission latency of the network1. Alternatively, the gain setting unit64bsets the control gain on the basis of the distribution of the transmission latency. Alternatively, the gain setting unit64bsets the control gain on the basis of the distribution of the transmission latency and the distribution of the coefficients for the state quantity of the mobile object2. If the transmission latency of the network1is simply set to a fixed value, or if it is set to an assumed maximum value, the control to be executed would be conservative since the gain setting unit64bsets the control gain in consideration of the transmission latency with a low probability of occurrence. On the other hand, when the distribution of the transmission latency of the network1is adopted, the following performance of the mobile object2to the target trajectory can be improved since the gain setting unit64bsets the control gain in consideration of the occurrence probability of the transmission latency.

The control amount calculation unit64ccalculates a control amount for causing the mobile object2to follow the target trajectory on the basis of the mobile object information from the receiver62and the control gain. A method of setting the control gain by the gain setting unit64band a method of calculating the control amount by the control amount calculation unit64cwill be described later in detail with reference toFIG.11and Non-Patent Documents 1 to 3.

The control implementability determination unit64ddetermines continuation of control or suspension of control of the mobile object2on the basis of the transmission latency of the network1. Alternatively, the control implementability determination unit64ddetermines continuation of control or suspension of control of the mobile object2on the basis of the distribution of the transmission latency. Alternatively, the control implementability determination unit64ddetermines continuation of control or suspension of control of the mobile object2on the basis of the distribution of the transmission latency and the distribution of the coefficients for the state quantity of the mobile object2. The control implementability determination unit64doutputs the control amount for controlling the mobile object2, that is, the control amount from the control amount calculation unit64c, to the transmitter65when the determination result is continuation of control. When the determination result is suspension of control, the control implementability determination unit64dsets a value that causes the mobile object2to stop as the control amount, and outputs the control amount to the transmitter65. A method of determining continuation of control or suspension of control will be described later in detail.

FIG.4is a block diagram illustrating another example of a configuration of the first mobile object control calculation unit641according to the present embodiment. The first mobile object control calculation unit641includes the mobile object estimation unit64a, the gain setting unit64b, the control amount calculation unit64c, the control implementability determination unit64d, and a state quantity estimation unit64e.FIG.4differs fromFIG.3in that the first mobile object control calculation unit641includes the state quantity estimation unit64e. In the case where the remote control device6remotely controls two or more mobile objects2, the second mobile object control calculation unit642and the like similarly includes the mobile object estimation unit64a, the gain setting unit64b, the control amount calculation unit64c, the control implementability determination unit64d, and the state quantity estimation unit64e. The description is omitted since the configuration is the same asFIG.3except for the state quantity estimation unit64e.

The state quantity estimation unit64eestimates a second state quantity different from the first state quantity of the state quantity of the mobile object2on the basis of the mobile object information from the receiver62. The second state quantity represents the state quantity not acquired by the sensor. The state quantity estimation unit64eestimates the second state quantity by applying an observer, a Kalman filter, or the like, on the basis of the state equation and the mobile object information regarding the mobile object2. The remote control device6controls the mobile object2using the second state quantity that as well which is not acquired by the sensor, leading to the remote control of the mobile object2with higher accuracy.

When estimating the distribution of coefficients for the state quantity of the mobile object2, the mobile object estimation unit64amay use not only the mobile object information from the receiver62but also the second state quantity from the state quantity estimation unit64e.

The control amount calculation unit64ccalculates a control amount on the basis of the mobile object information from the receiver62, the second state quantity from the mobile object estimation unit64a, and the control gain from the gain setting unit64b.

FIG.5is a block diagram illustrating an example of a configuration of the first mobile object21according to the present embodiment. The first mobile object21includes a clock synchronization unit2a, an internal sensor2b, a transmitter2c, a receiver2d, a command value calculation unit2e, and an actuator2f. In the case where the remote control device6remotely controls two or more mobile objects2, the second mobile object22and the like similarly include the clock synchronization unit2a, the internal sensor2b, the transmitter2c, the receiver2d, the command value calculation unit2e, and the actuator2f.

The clock synchronization unit2asynchronizes the timing of data transmission/reception in cooperation with the clock synchronization unit41, the clock synchronization unit51, and the clock synchronization unit61.

The internal sensor2bis installed on the mobile object2and outputs the mobile object information. When the mobile object2is a vehicle, the internal sensor2bis, for example, a vehicle speed sensor21b, an Inertial Measurement Unit (IMU) sensor22b, a steering angle sensor23b, a steering torque sensor24b, and the like.

The transmitter2ctransmits the mobile object information from the internal sensor2bto the receiver62of the remote control device6via the network1.

The receiver2dreceives the control amount from the transmitter65of the remote control device6.

The command value calculation unit2econverts the control amount into a current value or the like on the basis of the mobile object information from the internal sensor2band the control amount from the receiver2d, and outputs the current value to the actuator2f. When the mobile object2is a vehicle, the actuator2fis an electric motor2i, a vehicle drive device2n, a brake control device2q, and the like. In this case, the command value calculation unit2ecalculates the current value to be supplied to the electric motor2iin order to cause a steering of the vehicle to follow the target steering amount, and outputs the calculation result to the electric motor2i. Also, the command value calculation unit2ecalculates a driving force and a braking force of the vehicle required for causing the acceleration of the vehicle to follow a target acceleration/deceleration amount, and outputs the calculation result to the vehicle drive device2nand the brake control device2q. The electric motor2i, the vehicle drive device2nand the brake control device2qwill be described later in detail with reference toFIG.6.

The mobile object2is, for example, a vehicle, a flight vehicle, an agricultural machine, or the like.FIG.6is a diagram illustrating an example of a configuration in which the mobile object2is a vehicle in the present embodiment.

A steering wheel2g, which is installed for a driver (i.e., operator) to operate the vehicle, is coupled to a steering shaft2h. A pinion shaft2tof a rack-and-pinion mechanism2jis connected to the steering shaft2h. A rack shaft2uof the rack-and-pinion mechanism2jis reciprocally movable in response to the rotation of the pinion shaft2t, and front knuckles2mare connected to both left and right ends thereof via tie rods2k. The front knuckles2mrotatably support front wheels2vas steering wheels, and are steerably supported to the vehicle body frame.

The torque generated by the driver operating the steering wheel2grotates the steering shaft2h, and the rack-and-pinion mechanism2jmoves the rack shaft2uin the left-right direction in response to the rotation of the steering shaft2h. The movement of the rack shaft2ucauses the front knuckles2mto rotate around kingpin shafts (not illustrated), thereby causing the front wheels2vto turn in the left-right direction. Therefore, the driver can change an amount of lateral movement of the vehicle by operating the steering wheel2gwhen the vehicle moves forward or backward.

The vehicle is provided with the vehicle speed sensor21b, the IMU sensor22b, the steering angle sensor23b, a steering torque sensor24b, and the like, as the internal sensor2bfor acknowledging the traveling state of the vehicle.

The vehicle is also provided with actuators such as the electric motor2ifor implementing lateral motion of the vehicle, the vehicle drive device2nfor controlling longitudinal motion of the vehicle, and the brake control device2q.

Typically, the electric motor2iis configured by a motor and a gear, and is capable of freely rotating the steering shaft2hby applying torque to the steering shaft2h. In other words, the electric motor2ican freely steer the front wheels2vindependently of the operation of the steering wheel2gby the driver.

The vehicle drive device2nis an actuator2ffor driving the vehicle in the longitudinal direction. The vehicle drive device2nrotates the front wheels2vand rear wheels2wwith driving force obtained from a driving source such as an engine or a motor via a transmission (not illustrated) and a shaft2o. Accordingly, the vehicle drive device2ncan freely control the driving force of the vehicle.

Meanwhile, the brake control device2qis an actuator2ffor braking the vehicle, and controls the brake amounts of the brakes2rinstalled on the front wheels2vand the rear wheels2wof the vehicle. A typical brake2rgenerates a braking force using hydraulic pressure to press a pad against a disk rotor that rotates together with the front wheels2vand the rear wheels2w.

It is assumed that the internal sensor2band the plurality of devices described above comprise a network using a Controller Area Network (CAN), a Local Area Network (LAN), or the like in the vehicle. The devices can obtain the respective information via the network1. In addition, the internal sensor2bis capable of mutually transmitting and receiving data via the network1.

The configuration when the mobile object2is a vehicle has been described with reference toFIG.6, and the configuration is the same when the mobile object2is other than a vehicle.

The method by which the trajectory generation unit63generates the target trajectory will be described with reference toFIGS.7and8.FIG.7(a)andFIG.7(b)are diagrams illustrating an example of a target trajectory generation method according to the present embodiment.FIG.7(a)is a schematic diagram illustrating a case where an obstacle40exists in front of the mobile object2while traveling.FIG.7(b)is a diagram illustrating a case where the target route T1for generating a target trajectory of the mobile object2when the obstacle40exists ahead.FIG.8(a)andFIG.8(b)are diagrams illustrating an example of another target trajectory generation method according to the present embodiment.FIG.8(a)is a schematic diagram illustrating a case where a stop line50aand a traffic light50bexist in front of the mobile object2while traveling.FIG.8(b)is a diagram illustrating the target speed AY1 for generating a target trajectory of the mobile object2when the stop line50aand the traffic light50bexist ahead. InFIG.8(b), the horizontal axis represents the traveling distance AX1when the mobile object2travels toward the stop line50a, and the vertical axis represents the target speed AY1.

As illustrated inFIG.7(a), it is assumed that a plurality of sensors (here, sensors42and43in the object information acquisition unit4) are installed around the mobile object2, and detection ranges of the respective sensors are represented by R42and R43. The sensor42detects the relative position and the relative speed of the mobile object2with respect to the sensor42, and the sensor43detects the relative position and the relative speed of the obstacle40with respect to the sensor43. The trajectory generation unit63generates the target route T1as illustrated inFIG.7(b)on the basis of these pieces of information. The target route T1is a route for the mobile object2to avoid the obstacle40and is a route for traveling within a travelable area S1. Although not illustrated here, the trajectory generation unit63also generates a target speed of the mobile object2. As an example, the trajectory generation unit63generates a target speed so that the mobile object2slows down when avoiding the obstacle40. The trajectory generation unit63generates a target trajectory (avoidance trajectory) in which the target route T1and the target speed are combined.

As illustrated inFIG.8(a), it is assumed that a plurality of sensors (here, the sensor42in the object information acquisition unit4and a sensor52in the environment information acquisition unit5) are installed around the mobile object2, and detection ranges of the respective sensors are represented by R42and R52. The sensor42detects the relative position and the relative speed of the mobile object2with respect to the sensor42, and the sensor52detects the relative position of the stop line50aand the traffic light50bwith respect to the sensor52. Also, it is assumed that the sensor52detects that the traffic light50bis red. The trajectory generation unit63generates the target route (not illustrated) on the basis of these pieces of information. The target route is a route along which the mobile object2travels straight toward the stop line50a. Further, as illustrated inFIG.8(b), the trajectory generation unit63generates the target speed so that the target speed AY1 of the mobile object2is to be the one-dot chain line L1. The target speed AY1 is a speed in which the speed of the mobile object2is gradually decelerated to zero at the stop line50a. The trajectory generation unit63generates a target trajectory (stopping trajectory) in which the target route and the target speed AY1 are combined.

As illustrated inFIGS.7and8, the target trajectory is an avoidance trajectory with respect to the obstacle40and a stopping trajectory until the mobile object2stops. The target trajectory is not limited to these two trajectories, and there are various types thereof according to the road on which the mobile object2travels. In this manner, the trajectory generation unit63generates the target trajectory for the mobile object2, so that early-stage monitoring as to whether the mobile object2is traveling along the target trajectory is ensured, thereby implementing smooth traveling of the mobile object2. Although it is conceivable that the mobile object2per se generates the target trajectory, it is preferable that the trajectory generation unit63generates the target trajectory in terms of making the mobile object2versatile. This also brings the effect of simplifying the configuration of the mobile object2. InFIGS.7and8, although one mobile object2is illustrated, even if there are two or more mobile objects2, the respective target trajectories are generated by the same method.

Next, the method by which the trajectory generation unit63generates target trajectories for the respective two or more mobile objects2will be described with reference toFIGS.9and10.FIG.9is a diagram illustrating an example of a target trajectory generation method for two or more mobile objects2according to the present embodiment.FIG.10is a diagram illustrating an example of another target trajectory generation method for two or more mobile objects2according to the present embodiment.

FIG.9is a diagram illustrating the target trajectory generation method when the mobile objects2(here, a first mobile object21and a second mobile object22) travel through an intersection. It is assumed that a plurality of sensors (here, the sensor42in the object information acquisition unit4and the sensor52in the environment information acquisition unit5) are installed around the mobile objects2, and detection ranges of the respective sensors are represented by R42and R52. The sensor42detects the relative positions and the relative speeds of the first mobile object21and the second mobile object22with respect to the sensor42, and the sensor52detects the relative position of the stop line50awith respect to the sensor52. The trajectory generation unit63generates the target route T11for the first mobile object21on the basis of these pieces of information. Although not illustrated here, the trajectory generation unit63also generates the target speed of the first mobile object21. The trajectory generation unit63generates the target speed such that the first mobile object21has a constant speed along the target route T11. Also, the trajectory generation unit63generates a target route T12for the second mobile object22. Although not illustrated here, the trajectory generation unit63also generates the target speed of the second mobile object22. The target speed for the second mobile object22is a speed that is gradually decelerated as it approaches the stop line50aand reaches zero at the stop line50a. The trajectory generation unit63generates a target trajectory in which the target route T11and the target speed for the first mobile object21are combined. Similarly, the trajectory generation unit63generates a target trajectory in which the target route T12and the target speed for the second mobile object22are combined.

InFIG.9, the trajectory generation unit63generates a target trajectory in which travel priorities of the mobile objects2are considered. In this case, the target trajectories for the first mobile object21and the second mobile object22are generated such that the first mobile object21has a higher traveling priority from the stop line50ato be detected by the sensor52.

FIG.10is a diagram illustrating the target trajectory generation method when the mobile objects2(here, the first mobile object21and the second mobile object22) travel in column formation. It is assumed that a sensor (here, the sensor42in the object information acquisition unit4) is installed around the mobile objects2, and a detection range of the sensor42is represented by R42. The sensor42detects the relative positions and the relative speeds of the first mobile object21and the second mobile object22with respect to the sensor42. The trajectory generation unit63generates the target route T11of the first mobile object21on the basis of these pieces of information. Although not illustrated here, the trajectory generation unit63also generates the target speed of the first mobile object21. As an example, the trajectory generation unit63generates the target speed such that the first mobile object21has a constant speed along the target route T11. Also, the trajectory generation unit63generates the target route T12for the second mobile object22. Although not illustrated here, the trajectory generation unit63also generates the target speed of the second mobile object22. The target speed for the second mobile object22is the same as the target speed for the first mobile object21. The trajectory generation unit63generates a target trajectory in which the target route T11and the target speed for the first mobile object21are combined. Similarly, the trajectory generation unit63generates a target trajectory in which the target route T12and the target speed for the second mobile object22are combined.

InFIG.10, the trajectory generation unit63generates a target trajectory in which, with respect to the first mobile object21, which is a leader of the mobile objects2, the second mobile object22other than the leader forms a column.

As described with reference toFIGS.9and10, the trajectory generation unit63generates the target trajectory for a plurality of mobile objects2. Accordingly, even if the transmission latency is large, early-stage monitoring as to whether the mobile object2is traveling along the target trajectory is ensured, thereby implementing smooth traveling of the mobile object2. Although it is conceivable that each mobile object2generates a target trajectory, high efficiency and reduction in calculation load are expected by the trajectory generation unit63collectively generating the target trajectory.

Next, a method of setting a control gain by the gain setting unit64band a method of calculating a control amount by the control amount calculation unit64cwill be described with reference toFIG.11and Non-Patent Documents 1 to 3.

FIG.11is a block diagram illustrating an example of a configuration in which the remote control device6controls the mobile object2in the present embodiment. InFIG.11, the solid lines mean the input/output of the signal represented by the continuous system, and the dashed line means the input/output of the signal represented by the discrete system.

The mobile object information of the mobile object2acquired by the sensor is a discrete value; therefore, the mobile object information corresponds to an output value of a sampler6d. The mobile information is transmitted to the remote control device6via the network1; therefore, transmission latency (upload transmission latency6bhere) occurs at this moment. The mobile object information is input to a control unit6awith latency of this upload transmission latency. The control unit6aoutputs a control amount calculated using the control gain on the basis of the mobile object information. The control amount corresponds to the control amount output by the control amount calculation unit64c. The control mount is transmitted to the mobile object2via the network1; therefore, transmission latency (download transmission latency6chere) occurs at this moment. The control amount to be input to the mobile object2at a certain time is kept a constant value by a holder6euntil the next input. That is, the holder6ehas a zero-order hold function. The control amount being zero-order hold is input to the mobile object2.

A closed loop system is illustrated inFIG.11; therefore, in order to secure control stability, it is required that the control gain is set in consideration of the transmission latency (upload transmission latency6band download transmission latency6c), and the control amount is calculated. Control design utilizing the transmission latency being expressed using probability distributions will be described below. In this case, the control gain is set in consideration of the control stability regarding the probability distributions of the transmission latency, and the control amount is calculated.

A discrete-time state equation of the mobile object2is determined by a random variable as illustrated in the following Expression (1).

In Expression (1), k represents an integer greater than or equal to 0, xkrepresents a state quantity of mobile object2at time tk, ukrepresents an amount of control for mobile object2, ξkrepresents a value of a random variable at time tk, and Bk(ξk) represent random matrices determined by ξk.

According to Non-Patent Documents 1 to 3, if there exist a and λ that satisfy the following Expression (2), for any positive integer k and any real vector x0, the closed loop system is second-order moment exponentially stable, i.e. stable with respect to the probability distribution.

In Expression (2), a represents a positive real number, ? represents a real number from 0 to 1, ∥xk∥ represents the Euclidean norm of the vector xk, and E represents the expected value of the random variable. Further, the control amount ukis expressed by the following Expression (3) using the control gain F.

At this point, the condition for the existence of the control gain F that satisfies the second-order moment exponential stability is existence of a positive definite matrix V, a real matrix W, and λ, that satisfy the following Expression (3).

In Expression (4), T represents the transpose and I represents the identity matrix. HAand HBrepresent matrices defined by Expressions (5) to (7) below.

In Expressions (5) to (7), n is a natural number, HAi(i=1, . . . ,n) and HBirepresent real matrixes. HABrepresents a real matrix that satisfies Expression (9) with respect to the matrix GABdefined by Expression (8) below.

In Expression (8), row(Ak(ξ0)) represents a row vector in which the elements of matrix Ak(ξ0) are arranged in order from the first row.

If the closed loop system satisfies second-order moment exponential stability, the control gain F is given by the following Expression (10).

The control gain F and the control amount ukcan be obtained from Expressions (3) and (10). In the above description, the closed loop system is represented by a stochastic system including the random variable, however, a control system represented by a deterministic system (hereinafter referred to as “deterministic system control”) can be fused with respect to this. In this case, the control gain F is set in consideration of not only the second-order moment exponential stability but also the stability of the deterministic system control. The deterministic system control includes known control system, such as H∞control and H2control. Here, taking the H2control as an example, a method of setting the control gain F in the entire system will be introduced.

When considering control stability in a system, firstly, the stochastic system is replaced with the deterministic system. Then, the discrete-time state equation of the mobile object2is determined as illustrated in the following Expressions (11) and (12).

In Expressions (11) and (12), ξerepresents a value ξkof a certain random variable, which is a fixed value that does not change with time. ξemay be an average value or a median value obtained from the distribution of ξkrepresents an evaluation output at time tk, and wkrepresents a disturbance input at time tk. A(ξe), B(ξe), C and D represent time-invariant matrixes. Also, G(s) is assumed to represent the transfer function matrix from the disturbance input wkto the evaluation output zk. s represents the Laplacian operator. Also, D=0. In this case, the condition that the system requires is the real part of all eigenvalues of matrix A being negative, and ∥G∥(s)2<α(α>0), which is the norm of G(s), being established. This condition is equivalent to the existence of a semi-positive definite matrix P and a positive definite matrix Z that satisfy the linear matrix inequalities of Expressions (13) to (15) below.

In Expressions (15), trace(Z) represents the sum of the diagonal elements of the matrix Z. When H2 control is fused to the stochastic system, the control gain F is required to be set, in consideration of the second-order moment exponential stability of Expressions (2) and (4) and the linear matrix inequalities of Expressions (13) to (15). Although the H2control is taken as an example here, the same applies to the H∞control. Accordingly, the gain setting unit64bsets the control gain F in consideration of the control stability regarding the distribution of the transmission latency and a system performance condition expressed by linear matrix inequalities.

As for the stochastic system, the control gain F may be set in consideration of not only the probability distribution of transmission latency but also the probability distribution of coefficients with respect to the state quantity of the mobile object2. In this case, the second-order moment exponential stability of Expressions (2) and (4) is applied to the probability distribution of transmission latency and the probability distribution of coefficients. Also, the gain setting unit64bsets the control gain F in consideration of the control stability regarding the distribution of the transmission latency, the control stability regarding the distribution of coefficients, and a system performance condition expressed by linear matrix inequalities.

Note, there may be a case where no control gain F that satisfies the second-order moment exponential stability. In such a case, therefore, the control implementability determination unit64dperforms determination of control stop for the mobile object2. In order to determine whether or not the closed loop system is second-order moment exponentially stable, the eigenvalues of the matrix on the left side of Expression (4) are calculated and whether or not the minimum eigenvalue is positive is determined. Alternatively, the control implementability determination unit64dmay perform the determination of control stop for the mobile object2when the absolute value of a difference between a cumulant of the distribution of the transmission latency estimated by mobile object estimation unit64aand a cumulant of the distribution of the transmission latency when the control gain F is designed is greater than or equal to a specified value. Here, a cumulant is a value indicating characteristics of distribution. The cumulant may be a combination of the distribution of the transmission latency and the distribution of the coefficients for the state quantity of the mobile object2. Alternatively, the control implementability determination unit64dmay perform the determination of control stop for the mobile object2when transmission latency greater than transmission latency with a predetermined probability occurs in the distribution of pre-estimated transmission latency. Alternatively, the control implementability determination unit64dmay perform the determination of control stop for the mobile object2when an error greater than a coefficient error with a predetermined probability occurs in the distribution of pre-estimated coefficients. As a result, the mobile object2can be normally controlled even when a problem arises in control stability.

When obtaining the control gain F and the control amount ukin the closed loop system including the probability distribution of the transmission latency, the discrete-time state equation of the mobile object2illustrated in Expression (1) is the starting point. However, the control gain F and the control amount ukare typically obtained with the continuous-time state equation of the mobile object2as a starting point. Accordingly, a method of obtaining the control gain F and the control amount ukon the basis of the continuous-time state equation will be described.

Then, the continuous-time state equation of the mobile object2is determined as illustrated in the following Expression (16).

In Expression (16), xcrepresents the state quantity of the mobile object2in continuous time, ucrepresents a control amount in continuous time, xcrepresents a value obtained by time derivative xc, and Acand Bcrepresent matrixes. The continuous-time state equation of Expression (16) is converted into a discrete-time state equation according to the sampling interval hk(=tk+1−tk) at time tk. However, the sampling interval hkis determined not only by the transmission latency of the upload transmission latency6band the download transmission latency6c, but also by the transmission latency when the signal transmission between each element inFIG.11. The sampler6dand the holder6etransform Expression (16) into a discrete-time state equation as illustrated in Expression (17) below.

In Expression (17), Akand Bkare given to Expressions (18) and (19) below.

Since AKand B K are represented using sampling interval hkin Expression (18) and Expression (19), a random matrix that depends on the value ξkof the probable variable. In Expression (17), an enlarged system in which new state quantity X0K=UK−1is added to Expression (17) since the control amount is not UKbut UK−1. The enlarged system is expressed by following Expression (20).

In Expression (20), xe,k, Aeand Be, are expressed by Expressions (21) to (23).

Since Expression (20) has the same form as the discrete-state equation such as Expression (1), the control gain F and the control amount UKin consideration of the secondary-order moment exponentially stable can be obtained using Expression (20).

Next, when the mobile object2is a vehicle, a method of obtaining the control gain F and the control amount ukwill be described.FIG.12is a schematic diagram illustrating an example of a vehicle model according to the present embodiment. InFIG.12, the horizontal axis X and the vertical axis Y represent the position of the center of gravity of the vehicle in the inertial coordinate system. Xband Ybare the coordinate system based on the longitudinal and lateral directions of the vehicle. eyand eθare, respectively, the lateral deviation and the angle of deviation of the vehicle relative to the target route T1. The continuous-time state equation for the lateral direction of the vehicle is expressed by Expression (24) below.

In Expression (24), vxrepresents a vehicle speed, δ represents a steering angle, m represents a mass, Lfrepresents a distance from the vehicle center of gravity to the front wheel2v, Lrrepresents a distance from the center of gravity of the vehicle to the rear wheel2w, Izrepresents the moment of inertia around the yaw axis, Cfrepresents the cornering stiffness of the front wheels2v, and Crrepresents the cornering stiffness of the rear wheels2w. Cornering stiffness is a proportional coefficient representing the relationship between the lateral force generated in the vehicle and the sideslip angle, and is a value that varies depending on road conditions (dry, wet, frozen, etc.), for example.

From Expression (24), the vehicle can follow the target route in the lateral direction by controlling ey, eθ, ey, and eθto be zero. Further, the continuous-time state equation for the longitudinal direction of the vehicle is expressed by Expression (25) below.

In Expression (25), axrepresents a longitudinal acceleration, uarepresents a target acceleration in the longitudinal direction, and T a represents the time constant of the first-order lag system. Expression (25) corresponds to the continuous-time state equation of Expression (16). Expression (25) is converted into a discrete-time state equation according to the sampling interval hkthat is affected by the transmission latency of the network1. Then, the control gain F that minimizes the evaluation function represented by the vehicle speed vx, the longitudinal acceleration ax, and the target acceleration uais determined while taking into consideration of the second-order moment exponential stability of Expressions (2) and (4). In other words, the control gain F is obtained in consideration of the transmission latency with Expression (25) as a regulator problem. At this point, not only the distribution of the transmission latency but also the distribution of the coefficients with respect to a vehicle state quantity may be considered. Also, the H2control or the H∞control may be combined and a condition regarding the control stability thereof may be added.

FIG.13is a flowchart illustrating an example of a procedure for remote control according to the present embodiment.

As illustrated inFIG.13, when the remote control of the mobile object2starts by a means (not illustrated), the receiver62receives mobile object information and surrounding information (Step ST1).

The trajectory generation unit63generates a target trajectory on the basis of the map data from the map database7and the surrounding information from the receiver62(Step ST2).

The mobile object estimation unit64aestimates the transmission latency (Step ST3). The mobile object estimation unit64amay estimate the distribution of the transmission latency, or may estimate the distribution of the coefficients for the state quantity of the mobile object2.

The gain setting unit64bsets a control gain on the basis of the transmission latency of the network1(Step ST4). The gain setting unit64bmay set the control gain on the basis of the distribution of the transmission latency or may set the control gain on the basis of the distribution of the transmission latency and the distribution of the coefficients for the state quantity of the mobile object2.

The control amount calculation unit64ccalculates a control amount on the basis of the mobile object information from the receiver62and the control gain (Step ST5).

The control implementability determination unit64ddetermines continuation of control or suspension of control on the basis of the transmission latency from the mobile object estimation unit64a(Step ST6). The control implementability determination unit64dmay perform the determination on the basis of the distribution of the transmission latency, or may perform the determination on the basis of the distribution of the transmission latency and the distribution of the coefficients for the state quantity of the mobile object2. When the determination result is suspension of control, the control implementability determination unit64dsets a value that causes the mobile object2to stop as the control amount.

The transmitter65outputs the control amount from the control implementability determination unit64dto the mobile object2(Step ST7).

An unillustrated means determines whether or not to continue the remote control (Step ST8).

When the determination in Step ST8 is “Yes”, the process returns to Step ST1 to continue remote control. When the determination in Step ST8 is “No”, the remote control ends.

According to the embodiment described above, smooth traveling can be implemented since the remote control device6generates the target trajectory of the mobile object2.

Here, a hardware configuration of the remote control device6in the present embodiment will be described. Each function of the remote control device6may be implemented by a processing circuit. The processing circuit includes at least one processor and at least one memory.

FIG.14is a diagram illustrating the hardware configuration of the remote control device6according to the present embodiment. The remote control device6can be implemented by a processor8and a memory9illustrated inFIG.14(a). The processor8is, for example, a Central Processing Unit (also referred to as CPU, central processing unit, processor, arithmetic unit, microprocessor, microcomputer, processor, Digital Signal Processor (DSP)) or system Large Scale Integration (LSI).

The memory9is, for example, a non-volatile or volatile semiconductor memory, such as a Random Access Memory (RAM), a Read Only Memory (ROM), a flash memory, an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM (registered trademark)), or the like, a Hard Disk Drive (HDD), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a digital versatile disc (DVD) or the like.

The function of each unit of the remote control device6is implemented by software (software, firmware, or software and firmware). Software etc. is written as a program and stored in the memory9. The processor8reads out and executes the program stored in the memory9, thereby implementing the function of each unit. In other words, it can be said that the program causes a computer to execute the procedure or the method of the remote control device6.

The program executed by the processor8may be stored in a computer-readable storage medium in an installable or executable format and provided as a computer program product. Also, the program executed by processor8may be provided to the remote control device6via a network such as the Internet.

Also, the remote control device6may be implemented by a dedicated processing circuit10illustrated inFIG.14(b). When dedicated hardware is applied to the processing circuit10, the processing circuit10corresponds, for example, to a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an Application Specific Integrated Circuit (ASIC), or a Field-Programmable Gate Array (FPGA), or the combination thereof.

The configuration in which the functions of the components of the remote control device6are implemented by any one of software or the like and hardware has been described above. However, the configuration is not limited thereto, a configuration in which some components of the remote control device6are implemented by software or the like and some other components are implemented by dedicated hardware may be adoptable.

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