JP6668915B2 - Automatic operation control system for moving objects - Google Patents

Description

  The present invention relates to an automatic operation control system for a moving object.

  A mobile robot that moves in a room, has map information having information on the position and size of obstacles in the room such as furniture, and maps a travel route from a current position to a target while avoiding furniture. There is a known mobile robot that determines the position of a moving robot and moves along a moving path (see Patent Document 1).

JP 2003-345438A

  When the obstacle in the room is a static obstacle whose position is hardly changed like a bed, for example, if the map information includes information on the position and the size of the obstacle, the mobile robot can move the obstacle. You may be able to move around. However, if the obstacle is a static obstacle whose position changes relatively frequently, for example, a chair or a trash can, even if the static obstacle exists at a certain position at a certain time, another one may be used. At the time, the static obstacle is unlikely to exist at the certain position, and is likely to exist at a position different from the certain position. If the obstacle is a dynamic obstacle such as a human or a pet, the position is more likely to have changed.

  The map of Patent Literature 1 merely has information on the position and size of the obstacle at the time when the map information is created. Therefore, in Patent Literature 1, there is a possibility that the position of the obstacle that changes with time, that is, the situation in the room, cannot be accurately grasped. In other words, if the information included in the map information is only the information on the position and the size of the obstacle, it is difficult to accurately grasp the state of the space in which the mobile robot moves.

  By the way, for example, when the driver cannot perform manual driving, such as when the driver is in a faint state, it is necessary to stop the vehicle automatically. In this case, if the vehicle is stopped in the lane, the following vehicle may collide with the host vehicle. Therefore, when stopping the vehicle automatically, it is necessary to stop in an area suitable for stopping the vehicle, and therefore, it is necessary to more accurately determine an area suitable for stopping the vehicle.

  When an area in the space suitable for stopping the moving object is referred to as a stop adaptation area, an object of the present invention is to provide an automatic operation control system for a moving object that can more accurately determine the stop adaptation area. It is in.

  According to the present invention, there is provided an automatic driving control system for a mobile body, comprising: an environmental map storage device storing environmental map information; and an electronic control unit, wherein the environmental map information includes a plurality of Position information representing the position of each of the plurality of positions, the state quantity representative value of each of the plurality of positions, the state quantity representative value associated with the corresponding position information, and the state quantity of each of the plurality of positions. And the state quantity variability associated with the corresponding position information, and the state quantity variability is the easiness of change of the state quantity of the corresponding position with respect to time. The electronic control unit is configured to determine a stop adaptation area suitable for stopping the moving object based on the state quantity representative value and the state quantity variability of the environment map information. Is and comprising a stop adapted region determining unit, the automatic operation control system of the moving body is provided.

  The stop adaptation area can be determined more accurately.

It is a block diagram of the automatic operation control system of the mobile of 1st Example by this invention. It is a schematic diagram explaining an external sensor. It is a block diagram of an automatic operation control part of a 1st example by the present invention. It is a diagram explaining a course. FIG. 4 is a schematic diagram showing environmental map information of the first embodiment according to the present invention. It is a figure showing an example of change with time of a state quantity. It is a figure which shows another example of the change with respect to time of a state quantity. It is a figure which shows another example of the change with respect to time of a state quantity. It is the schematic explaining the detection method of position information and a state quantity. It is a time chart explaining the example of calculation of state quantity variability. It is a time chart explaining the example of calculation of state quantity variability. It is a figure showing an example of a plane map. FIG. 9B is a schematic diagram showing state quantity representative values and state quantity variability in various regions of the place shown in FIG. 9A. It is a schematic diagram explaining course P of a 1st example by the present invention. 4 is a flowchart illustrating an automatic operation control routine according to the first embodiment of the present invention. 5 is a flowchart illustrating a stop request control routine according to the first embodiment of the present invention. It is a block diagram of the automatic operation control system of the mobile of 2nd Example by this invention. 9 is a flowchart illustrating a stop request control routine according to a second embodiment of the present invention. FIG. 10 is a block diagram of a mobile object automatic operation control system according to a third embodiment of the present invention. It is a schematic diagram explaining course P of a 3rd example by the present invention. 9 is a flowchart illustrating a stop request control routine according to a third embodiment of the present invention.

  FIG. 1 is a block diagram showing an automatic operation control system for a moving object according to a first embodiment of the present invention. The moving object includes a vehicle, a mobile robot, and the like. Hereinafter, a case where the moving body is a vehicle will be described as an example. Referring to FIG. 1, an automatic driving control system for a vehicle includes an external sensor 1, a GPS receiving unit 2, an internal sensor 3, a map database 4, a storage device 5, an environment map storage device 6, a navigation system 7, an HMI (Human Machine Interface). 8, various actuators 9, an electronic control unit (ECU, Electronic Computer Unit) 10, and a driver state sensor 21.

  The external sensor 1 is a detection device for detecting information on the outside or surroundings of the vehicle. The external sensor 1 includes at least one of a lidar (LIDAR: Laser Imaging Detection and Ranging), a radar (Radar), and a camera. In a first embodiment according to the invention, as shown in FIG. 2, the external sensor 1 comprises at least one rider SO1, at least one radar SO2, and at least one camera SO3.

  The rider SO1 is a device that detects an object outside the host vehicle V using laser light. In the first embodiment according to the present invention, the object is a static object that is an immovable object (for example, a building or a road), a dynamic object that is a movable object (for example, another vehicle, a pedestrian, etc.), Includes quasi-static objects that are basically immovable but easily movable objects (eg, standing signs, trash cans, tree branches, etc.). In the example shown in FIG. 2, a single rider SO1 is installed on the roof of the vehicle V. In another embodiment (not shown), for example, four riders are respectively attached to the bumpers at the four corners of the vehicle V. The rider SO1 sequentially irradiates the entire periphery of the vehicle V with laser light and measures information on the object from the reflected light. This object information includes the distance and direction from the rider SO1 to the object, that is, the relative position of the object with respect to the rider SO1. The object information detected by the rider SO1 is transmitted to the electronic control unit 10. On the other hand, the radar SO2 is a device that detects an object outside the host vehicle V using radio waves. In the example shown in FIG. 2, for example, four radars SO2 are respectively attached to the bumpers at the four corners of the vehicle V. The radar SO2 emits a radio wave from the radar SO2 around the own vehicle V, and measures information about an object around the own vehicle V from the reflected wave. The object information detected by the radar SO2 is transmitted to the electronic control unit 10. In the example shown in FIG. 2, the camera SO3 includes a single stereo camera provided inside the windshield of the vehicle V. The stereo camera SO3 captures a color or monochrome image of the front of the host vehicle V, and information of the color or monochrome image captured by the stereo camera SO3 is transmitted to the electronic control unit 10.

  Referring again to FIG. 1, the GPS receiving unit 2 receives signals from three or more GPS satellites, and thereby determines the absolute position of the own vehicle or the external sensor 1 (for example, the latitude, longitude, and altitude of the own vehicle V). Detect the information that represents. The absolute position information of the own vehicle detected by the GPS receiver 2 is transmitted to the electronic control unit 10.

  The internal sensor 3 is a detection device for detecting a traveling state of the vehicle V. The running state of the host vehicle V is represented by at least one of the speed, acceleration, and attitude of the host vehicle. The internal sensor 3 includes one or both of a vehicle speed sensor and an IMU (Inertial Measurement Unit). In a first embodiment according to the invention, the internal sensor 3 comprises a vehicle speed sensor and an IMU. The vehicle speed sensor detects the speed of the host vehicle V. The IMU includes, for example, a three-axis gyro and a three-direction acceleration sensor, detects the three-dimensional angular velocity and acceleration of the own vehicle V, and detects the acceleration and attitude of the own vehicle V based on the three-dimensional angular velocity and acceleration. The traveling state information of the own vehicle V detected by the internal sensor 3 is transmitted to the electronic control unit 10.

  The map database 4 is a database relating to map information. The map database 4 is stored in, for example, an HDD (Hard disk drive) mounted on the vehicle. The map information includes, for example, road position information, road shape information (e.g., types of curves and straight lines, curvatures of curves, positions of intersections, junctions, and junctions).

  The storage device 5 stores a three-dimensional image of the object detected by the rider SO1 and a road map dedicated to automatic driving created based on the detection result of the rider SO1. The three-dimensional images and road maps of these objects are constantly or regularly updated.

  The environment map storage device 6 stores environment map information (to be described later).

  The navigation system 7 is a device that guides the host vehicle V to a destination set by the driver of the host vehicle V via the HMI 8. The navigation system 7 calculates a target route to a destination based on the current position information of the vehicle V detected by the GPS receiver 2 and the map information in the map database 4. The information on the target route of the host vehicle V is transmitted to the electronic control unit 10.

  The HMI 8 is an interface for outputting and inputting information between the occupant of the host vehicle V and the automatic driving control system of the vehicle. In the first embodiment according to the present invention, the HMI 8 includes a display for displaying text or image information, a speaker for generating sound, and an operation button, a touch panel, or a voice recognition device (microphone) for an occupant to perform an input operation.

  The actuator 9 is a device for controlling the traveling operation of the own vehicle V according to a control signal from the electronic control unit 10. The driving operation of the vehicle V includes driving, braking, and steering of the vehicle V. The actuator 9 includes at least one of a driving actuator, a braking actuator, and a steering actuator. The drive actuator controls an output of an engine or an electric motor that provides a driving force of the vehicle V, and thereby controls a driving operation of the vehicle V. The brake actuator operates a braking device of the vehicle V, and thereby controls a braking operation of the vehicle V. The steering actuator operates the steering device of the vehicle V, and thereby controls the steering operation of the vehicle V.

  When an occupant performs an input operation to start automatic driving in the HMI 8 in a state where automatic driving is possible, a signal is sent to the electronic control unit 10 to start automatic driving. That is, driving, braking, and steering, which are driving operations of the vehicle V, are controlled by the actuator 9. On the other hand, when an input operation to stop automatic driving is performed by the occupant in the HMI 8, a signal is sent to the electronic control unit 10 to stop automatic driving, and at least one of the driving operations of the vehicle V is performed by the driver in manual driving. Is started. In other words, the automatic operation is switched to the manual operation. Incidentally, when the driver performs the driving operation of the vehicle V during automatic driving, that is, when the driver operates the steering more than a predetermined threshold amount, when the accelerator pedal is depressed more than the predetermined threshold amount, Alternatively, when the brake pedal is depressed by a predetermined threshold amount or more, the operation is switched from the automatic operation to the manual operation. Further, when it is determined that automatic driving is difficult during automatic driving, manual driving is requested to the driver via the HMI 7.

  The electronic control unit 10 is a computer including a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and the like, which are interconnected by a bidirectional bus. As shown in FIG. 1, an electronic control unit 10 according to a first embodiment of the present invention includes a storage unit 11 having a ROM and a RAM, an automatic operation control unit 12, a stop request determination unit 13, and a stop adaptation area determination unit 14. Is provided.

  The automatic driving control unit 12 is configured to control automatic driving of the vehicle V. The stop request determination unit 13 is configured to determine whether to stop the vehicle V. The stop adaptation area determination unit 14 is configured to determine a stop adaptation area suitable for stopping the vehicle V based on the environment map information in the environment map storage device 6.

  In the first embodiment according to the present invention, as shown in FIG. 3, the automatic driving control unit 12 includes a periphery recognition unit 12a, a self-position determination unit 12b, a route generation unit 12c, and a movement control unit 12d.

  The periphery recognition unit 12a is configured to recognize a situation around the host vehicle V using the external sensor 1. That is, the surrounding recognition unit 12a determines the surrounding state of the vehicle V based on the detection result of the external sensor 1 (for example, three-dimensional image information of the object by the rider SO1, object information by the radar SO2, photographing information by the camera SO3, and the like). Recognize. The external situation includes, for example, the position of the white line of the driving lane with respect to the vehicle V, the position of the center of the lane with respect to the vehicle V, the road width, the shape of the road (for example, the curvature of the driving lane, the change in the gradient of the road surface, etc.), the vehicle V (For example, information for distinguishing a static object from a dynamic object, the position of the object with respect to the vehicle V, the moving direction of the object with respect to the vehicle V, the relative speed of the object with respect to the vehicle V, and the like).

  The own position determination unit 12b is configured to determine the absolute position of the own vehicle V. That is, the self-position determining unit 12b determines the approximate position of the own vehicle V from the GPS receiving unit 2, the surrounding situation of the own vehicle V recognized by the surrounding recognition unit 12a, and the object stored in the storage device 5. The accurate absolute position of the vehicle V is calculated based on the information about the vehicle and a road map dedicated to automatic driving.

  The route generation unit 12c is configured to generate a route of the vehicle V. In the first embodiment according to the present invention, the course includes information representing the time t, information representing the absolute position (x (t), y (t)) of the vehicle at the time t, and traveling of the vehicle at the time t. It includes a combination (t, x (t), y (t), v (t), θ (t)) with information indicating a state (for example, speed v (t) and traveling direction θ (t)). Here, x (t) is represented by, for example, latitude, and y (t) is represented by, for example, longitude. For example, first, using the combination (0, x (0), y (0), v (0), θ (0)) at the current time (t = 0), the combination (Δt , X (Δt), y (Δt), v (Δt), θ (Δt)). Next, a combination (2Δt, x (2Δt), y (2Δt), v (2Δt), θ (2Δt)) after a further lapse of time Δt is calculated. Next, a combination (nΔt, x (nΔt), y (nΔt), v (nΔt), θ (nΔt)) after a further lapse of time nΔ is calculated. One example of these combinations is shown in FIG. That is, FIG. 4 shows the above-described combination (t, x (t), y (t), v) in a three-dimensional space defined by the time t and the absolute position (x (t), y (t)) of the vehicle V. (T), θ (t)) are plotted. As shown in FIG. 4, the path P is a curve obtained by sequentially connecting a plurality of combinations (t, x (t), y (t), v (t), θ (t)).

  The movement control unit 12d is configured to control the movement of the vehicle V. Specifically, the movement control unit 12d is configured to control the vehicle V to move along the path P generated by the path generation unit 12c. That is, the movement control unit 12d controls the actuator 9 so that the combination (t, x (t), y (t), v (t), θ (t)) of the course P is realized, and V drive, braking and steering are controlled.

  The driver state sensor 21 is a detection device for detecting the state of the driver. The state of the driver is represented by, for example, one or both of the appearance and the internal state of the driver. The appearance of the driver is represented, for example, by at least one of the driver's line of sight, the state of the driver's eyelids, the direction of the driver's face, and the driver's posture. The posture of the driver is represented by the position or orientation of the driver's body, the position of the driver's hand, or the like. On the other hand, the internal state of the driver is represented by a physiological index such as the driver's heart rate, blood pressure, and skin potential. When the driver's state is represented by the driver's line of sight, the state of the driver's eyelids, the direction of the driver's face, the driver's posture, and the like, the driver state sensor detects a driver camera mounted inside the vehicle V, for example. Prepare. This driver camera shoots the driver. When the state of the driver is represented by the internal state of the driver, the driver state sensor 21 includes, for example, an internal state sensor attached to the steering wheel. The internal state sensor detects, for example, a physiological index of the driver. Driver state information detected by the driver state sensor 21 is transmitted to the electronic control unit 10.

  In the first embodiment according to the present invention, the stop request determination unit 13 is configured to determine whether to stop the vehicle V based on the driver state detected by the driver state sensor 21. Specifically, it is determined whether or not the driver cannot perform the manual operation. For example, when the driver is in a dead state or a syncope state, it is determined that the driver cannot perform the manual operation. When it is determined that the driver cannot perform the manual driving, it is determined that the vehicle V should be stopped. In other words, a request to stop the vehicle V is output. On the other hand, when it is not determined that the driver cannot perform the manual driving, the request to stop the vehicle V is not output.

  When a stop request for the vehicle V is output from the stop request determination unit 13, the stop adaptation area determination unit 14 determines a stop adaptation area based on the environment map information in the environment map storage device 6. Next, the course generation unit 12c generates the course P such that the vehicle V stops in the stop adaptation area. Next, the movement control unit 12d controls the vehicle V so that the vehicle V moves along the course P. As a result, the vehicle V is automatically stopped in the stop adaptation area. Emergency evacuation is performed in this manner.

  On the other hand, when the stop request determination unit 13 does not output a stop request for the vehicle V, the route generation unit 12c generates a normal route P. That is, the course P is generated such that the vehicle V moves according to the above-described target route. In this case, the course P is generated so as to reach the destination safely and in the shortest time while observing laws and regulations.

  Next, environmental map information of the first embodiment according to the present invention will be described. FIG. 5 schematically shows environmental map information M of the first embodiment according to the present invention. As shown in FIG. 5, the environmental map information M of the first embodiment according to the present invention includes position information representing a plurality of positions in a space, state amount representative values associated with the corresponding position information, respectively. And state quantity variability associated with the corresponding position information. In the first embodiment according to the present invention, the above-mentioned space is a three-dimensional space. In another embodiment (not shown), the space is a two-dimensional space.

  The state quantity representative value and the state quantity variability at a certain position are calculated based on the state quantity at the certain position. In the first embodiment according to the present invention, the state quantity at a certain position is represented by the probability that an object exists at the certain position. In this case, the state quantity is calculated, for example, in the form of a continuous value from zero to one. In another embodiment (not shown), the state variables are calculated in the form of discrete values.

  The state quantity representative value at a certain position is a numerical value appropriately representing the state at the certain position. In the first embodiment according to the present invention, the state quantity representative value is calculated, for example, in the form of a continuous value from zero to one. In another embodiment (not shown), the state quantity representative value is calculated in the form of a discrete value.

  On the other hand, the state quantity variability at a certain position is a numerical value indicating the easiness of change of the state quantity at the certain position with respect to time. In the first embodiment according to the present invention, the state quantity variability is calculated in the form of a continuous value. In another embodiment (not shown), the state quantity variability is calculated in the form of discrete values. Next, the state quantity variability will be further described with reference to FIGS. 6A, 6B, and 6C. 6A, 6B, and 6C, the detected state quantities are plotted.

  The state quantity variability is represented by, for example, the frequency of change of the state quantity with respect to time or the degree of change. That is, the state quantity in the example shown in FIG. 6B has a higher frequency of change than the state quantity in the example shown in FIG. Therefore, the state quantity variability of the example shown in FIG. 6B is higher than the state quantity variability of the example shown in FIG. 6A. On the other hand, the state quantity of the example shown in FIG. 6C has a larger degree of change than the state quantity of the example shown in FIG. Therefore, the state variable in the example shown in FIG. 6C is higher than the state variable in the example shown in FIG. 6A.

  Next, an example of creating the environmental map information M will be described. In this creation example, an environment detection device that detects position information indicating a position in space and a state quantity of the position, a storage device for an environment map, and an electronic control unit for creating an environment map are provided. The electronic control unit for creation is configured to detect, with respect to each of the plurality of positions in the space, position information indicating the position and the state quantity of the position at different times from the environment detection device. An environment detection unit, a state amount calculation unit that calculates the state amount representative value using the detected state amount for each of the plurality of positions, and a state amount detected for each of the plurality of positions. A variability calculation unit configured to calculate the state quantity variability by using the state quantity representative value and the state quantity variability associated with the corresponding position information, respectively. A storage unit for storing in a storage device boundary map, using the environmental map creation systems with environmental map information M is created. The environmental mapping system is mounted on a moving object such as a vehicle. The environment detection device includes, for example, an external sensor (for example, a rider) that detects an object around the environment map creation system, an internal sensor, and a GPS receiver that detects an absolute position of the environment map creation system.

  FIG. 7 shows a case where the laser light emitted from the rider L of the environment map creation system is reflected by the object OBJ. In this case, a reflection point is formed at the position PX as shown by a black circle in FIG. The rider L measures relative position information of the position PX of the reflection point from the reflected light. From this measurement result, it can be seen that the object OBJ exists at the position PX. Therefore, the state quantity of the position PX, that is, the object existence probability is 1. Further, the absolute position information of the position PX can be known from the relative position information of the position PX from the rider 1 and the absolute position information of the environment map creation system from the GPS receiving unit of the environment map creation system. Further, it is found that no object exists at a position PY which is not a reflection point indicated by a white circle in FIG. 7, and therefore, the state quantity at the position PY, that is, the object existence probability becomes zero. Further, the absolute position information of the position PY can be known from the relative position information of the position PX from the rider L and the absolute position information of the environment map creation system from the GPS receiver of the environment map creation system. In this way, the absolute position information and the state quantities of the positions PX and PY are calculated.

In the example of creating the environmental map information M, the rider L of the environmental map creating system repeatedly detects object information at intervals of, for example, several tens of ms. In other words, the rider L of the environmental map creation system detects object information at a plurality of different times. Therefore, state quantities at a plurality of different times are calculated from the object information at a plurality of different times. Alternatively, even when a moving object equipped with the environmental map creating system moves a predetermined place a plurality of times, object information at a plurality of different times is detected, and therefore, a state quantity at a plurality of different times is calculated. 8A and 8B show various examples of the state quantity at a certain position at a plurality of different times.

  In the example of creating the environmental map information M, the amount of change in the state amount per unit time is calculated, and the state amount variability is calculated based on the amount of change in the state amount per unit time. That is, in the example shown in FIG. 8A, the change amounts (absolute values) dSQ1, dSQ2,... Of the state quantities in the same time width dt are calculated. The time width dt in this case is, for example, equal to the state quantity detection interval. In the example shown in FIG. 8A, the amount of change dSQ1, dSQ2,... Of the state quantity is calculated over a continuous time width dt, but in another example, the amount of change of the state quantity over a discontinuous time width dt. Are calculated respectively. Alternatively, in the example shown in FIG. 8B, the change amounts (absolute values) dSQ1, dSQ2,... Of the state quantities in a plurality of different time widths dt1, dt2,. The different time spans are, for example, on the order of seconds, minutes, days, years. Next, the amount of change dSQ1 / dt1, dSQ2 / dt2,... Per unit time of the state quantity is sequentially calculated. In the example shown in FIG. 8B, the change amounts dSQ1, dSQ2,... Of the state quantities are calculated in continuous time widths dt1, dt2,. Are calculated respectively. Next, the state quantity variability is calculated by performing a simple average or a weighted average of the change amounts dSQ1 / dt1, dSQ2 / dt2,... Per unit time of the state quantity. When the weighted average is used, in one example, the change amount per unit time dSQ / dt of the state quantity whose detection time is newer is weighted more heavily, and the change amount per unit time dSQ / dt of the state quantity whose detection time is older. Are weighted less. In another example, the change amount per unit time dSQ / dt of the state quantity whose detection timing is newer is weighted smaller, and the change amount per unit time dSQ / dt of the state quantity whose detection time is older is weighted larger. You. Such calculation of the state quantity variability is performed for each of a plurality of positions.

  In another example of the creation of the environmental map information M (not shown), a plurality of state quantities as a function of time are subjected to Fourier transform, and the state quantity variability is calculated from the result. Specifically, in one example, the intensity of a predetermined spectrum (frequency) is calculated as the state quantity variability. In another example, the state quantity variability is calculated by a simple average or a weighted average of the intensities of various spectra.

  On the other hand, in the example of creating the environmental map information M, the state quantity representative value is calculated based on the state quantity at a certain position detected at a plurality of different times. In one example, the state quantity representative value of a certain position is set to the latest state quantity of the certain position at a plurality of different times. In this way, the state quantity representative value at a certain position represents the latest state at the certain position. In another example, the state quantity representative value of a certain position is calculated by performing simple average or weighted average of the state quantity of the certain position at a plurality of different times. In this way, even if the state quantity at a certain position temporarily changes, the state at the position can be accurately represented by the state quantity representative value.

  Next, the state quantity representative values are stored in the storage device for the environment map in association with the corresponding position information. The state quantity variability is stored in the storage device for the environment map in association with the corresponding position information. Thus, the environmental map information M is created.

  Since the state quantity representative value and the state quantity variability are associated with the position information as described above, when the position information is designated, the state quantity representative value and the state quantity variability of the corresponding position can be found from the environment map information M. In the first embodiment according to the present invention, the environment map information M is a three-dimensional map because it has position information of a position in a three-dimensional space, a state quantity representative value, and a state quantity variability. In the first embodiment according to the present invention, the position information is absolute position information. In another embodiment (not shown), the position information is relative position information with respect to a predetermined specific position.

  The following can be understood from the environmental map information M created in this manner. That is, when the state quantity represented by the object existence probability at a certain position is large and the state quantity variability is low, the position is a static object (for example, a building, a road surface, or the like) or a stationary object. Occupied by a moving dynamic object (eg, another vehicle, a pedestrian, etc.) or a quasi-static object (eg, a signboard, a trash can, a tree branch, etc.). Alternatively, the occupancy state where the position is occupied by the dynamic or quasi-static object and the non-occupancy state where the position is not occupied by the dynamic or quasi-static object are switched relatively infrequently. At the same time, the occupation time is relatively long. On the other hand, when the state quantity at a certain position is small and the state quantity variability is low, nothing exists at the position. A specific example of such a position is a space above a pond. When the state quantity at a certain position is large and the state quantity variability is high, the occupation state and the non-occupation state are switched at a relatively high frequency at that position, and the occupation state time is relatively long. A specific example of such a position is a road with a relatively large traffic volume. When the state quantity at a certain position is small and the state quantity variability is high, the occupation state and the non-occupation state are switched at a relatively high frequency at that position, and the time of the non-occupation state is relatively long. An example of such a location is a road with relatively low (non-zero) traffic.

  That is, the environment map information M of the first embodiment according to the present invention includes not only information on the presence or absence of an object or an object at a certain position, but also information on the situation of the position. I have. Therefore, the situation in the space can be represented more accurately.

  In the first embodiment according to the present invention, the moving object equipped with the environmental map creating system is a moving object different from the vehicle V. In another embodiment (not shown), the moving object equipped with the environmental map creation system is a vehicle V. That is, the environment map information M is created in the vehicle V and stored in the environment map storage device 6. In this case, the external sensor 1 and the GPS receiver 2 of the vehicle V constitute an environment detection device of the environment map creation system.

  In the above-described first embodiment of the present invention, the state quantity at a certain position is represented by the probability that an object exists at the certain position. In another embodiment (not shown), the state quantity at a certain position is represented by the color or luminance value of an object present at a certain position. In this case, for example, it is possible to grasp which of the lamps of the traffic light is on. In this alternative embodiment, when the state quantity is represented by the color of the object, the color of the object is detected by a color camera as the camera SO3 of the external sensor 1. On the other hand, when the state quantity is represented by the luminance value of the object, the luminance value of the object is detected by the rider SO1, the radar SO2 of the external sensor 1, or the color or monochrome camera SO3. That is, the intensity of the reflected light obtained when the laser light emitted from the rider SO1 is reflected on the object represents the luminance value of the object. Similarly, the reflected wave intensity of the radar SO2 indicates the luminance value of the object. Therefore, the luminance value of the object is detected by detecting the intensity of the reflected light or the intensity of the reflected wave. When the state quantity is represented by the color of the object, the state quantity is quantified using, for example, an RGB model.

  On the other hand, in the above-described first embodiment of the present invention, one state information is associated with one state quantity variability. In another embodiment (not shown), a plurality of state quantity variabilities are associated with one piece of position information, and thus the environment map information M has a plurality of state quantity variabilities. In this case, in one example, as shown in FIG. 8B, a plurality of state quantity variabilities are calculated based on the change amounts of the state quantity in a plurality of different time widths. In another example, a plurality of state quantity variabilities are calculated based on a plurality of spectrum intensities obtained by performing a Fourier transform on the state quantity.

  As described above, the stop adaptation area determination unit 14 determines a stop adaptation area based on the environment map information M. In the first embodiment according to the present invention, in the first region where the state quantity representative value is smaller than the predetermined set representative value and the state quantity variability is lower than the predetermined set variability, An area adjacent to the second area whose value is larger than the set representative value and whose state quantity variability is lower than the set variability is determined as the stop adaptation area.

  As can be seen from the above description, no object is present in the first area where the state quantity representative value is small and the state quantity variability is low. Therefore, the vehicle V can be stopped in the first area. On the other hand, in the second area where the state quantity representative value is large and the state quantity variability is low, for example, a building is present. For this reason, the situation in the second area is stable. On the other hand, there is a possibility that the situation is unstable in the area where the state quantity variability is high and in the vicinity thereof.

  Then, the first area adjacent to the second area is considered to be a relatively safe place for stopping the vehicle V. Therefore, in the first embodiment according to the present invention, the first area adjacent to the second area is determined as the stop adaptation area. As a result, the stop adaptation region can be determined more accurately.

  Needless to say, the stop adaptation area needs to have an area larger than the area of the vehicle V projected on the road surface.

  Next, with reference to FIGS. 9A and 9B, a method of determining a stop adaptation region will be further described. FIG. 9A shows a planar map of a certain place. In FIG. 9A, PL indicates planting, BL indicates a building, PK indicates a parking lot, RW indicates a roadway, RS indicates a road shoulder, LM indicates a lane, and EM indicates a lane outside line.

  FIG. 9B shows the tendency of the state quantity representative value and the state quantity variability in various regions in the place shown in FIG. 9A. That is, in the area of the planting PL, the state quantity representative value is larger than the set representative value, and the state quantity variability is higher than the set variability. In FIG. 9B, this area is indicated by “LL”. On the other hand, in the area of the building BL, the state quantity representative value is larger than the set representative value, and the state quantity variability is lower than the set variability. In FIG. 9B, this area is indicated by “LS”. In the area of the parking lot PK, the state quantity representative value is smaller than the set representative value, and the state quantity variability is higher than the set variability. In FIG. 9B, this area is indicated by “SL”. In the area of the roadway RW, the state quantity representative value is smaller than the set representative value, and the state quantity variability is higher than the set variability. In FIG. 9B, this area is indicated by “SL”.

  Further, in the portion of the road shoulder RS area adjacent to the planting PL, the state quantity representative value is smaller than the set representative value, and the state quantity variability is higher than the set variability. In FIG. 9B, this area is indicated by “SL”. In the portion of the road shoulder RS area adjacent to the building BL, the state quantity representative value is smaller than the set representative value, and the state quantity variability is lower than the set variability. In FIG. 9B, this area is indicated by “SS”. In the portion of the road shoulder RS area adjacent to the parking lot, the state quantity representative value is smaller than the set representative value, and the state quantity variability is higher than the set variability. This is because vehicles come and go between the parking lot PK and the roadway RW. In FIG. 9B, this area is indicated by “SL”.

  Therefore, in the example shown in FIG. 9B, the area indicated by SS is the above-described first area R1, and the area indicated by LS is the above-described second area R2. For this reason, the first region R1 adjacent to the second region R2 is determined as the stop adaptation region ST.

  As described above, in the first embodiment of the present invention, when the stop request determination unit 13 outputs a stop request for the vehicle V, the route generation unit 12c determines the stop adaptation region ST determined by the stop adaptation region determination unit 14. The path P is generated such that the vehicle V stops within the path.

  When the stop adaptation area determination unit 14 determines one stop adaptation area ST, the path P is generated so that the vehicle V stops in the determined stop adaptation area ST. On the other hand, when the stop adaptation area determination unit 14 determines the plurality of stop adaptation areas ST, one stop adaptation area is selected from the plurality of stop adaptation areas ST, and the vehicle stops within the selected stop adaptation area ST. A path P is generated.

  In the first embodiment according to the present invention, the selection of the stop adaptation area ST in this case is performed based on the distance from the current position of the vehicle V to the stop adaptation area ST. For example, the stop adaptation area ST closest to the current position of the vehicle V is selected.

  FIG. 10 shows an example of the plurality of stop adaptation areas STX, STY, and STZ determined by the stop adaptation area determination unit 14. In the example shown in FIG. 10, the stop adaptation areas STX, STY, and STZ have different distances from the current position of the vehicle V. Specifically, the stop adaptation area STX is closest to the current position of the vehicle V, the stop adaptation area STY is second closest, and the stop adaptation area STZ is farthest from the current position of the vehicle V.

  Therefore, in the first embodiment according to the present invention, the stop adaptation area STX closest to the current position of the vehicle V is selected. Next, the route PX is generated such that the vehicle V stops in the stop adaptation region STX. When the stop adaptation area STX closest to the current position of the vehicle V is located behind the traveling direction of the vehicle V, the vehicle V may make a U-turn.

  However, in order to safely and reliably stop the vehicle V, the longitudinal acceleration or deceleration of the vehicle V is maintained within a certain range, and the lateral acceleration or deceleration of the vehicle V is within a certain range. It needs to be maintained. That is, the stop adaptation region is selected such that the longitudinal acceleration or deceleration of the vehicle V is maintained within a certain range, and the lateral acceleration or deceleration of the vehicle V is maintained within a certain range. . Therefore, in the first embodiment according to the present invention, the stop adaptation area STX closest to the current position of the vehicle V is selected while ensuring the safe and secure stop of the vehicle V. That is, in the example of FIG. 10, when it is difficult to safely and reliably stop the vehicle V in the nearest stop adaptation region STX, the second closest stop adaptation region STY is selected, and the vehicle V stops adaptation. The course PY is generated so as to stop in the area STY.

  The path P is generated such that the vehicle V moves around an obstacle recognized by the peripheral recognition unit 12a or avoids the vehicle V, and also prevents the vehicle V from hindering the traveling of another vehicle.

  FIG. 11 shows a routine for executing the automatic operation control of the first embodiment according to the present invention. This routine is repeatedly performed when the automatic operation control is to be performed. Referring to FIG. 11, in step 101, it is determined whether or not a request to stop the vehicle V has been output. When the stop request has been output, the routine proceeds to step 102, where the stop adaptation area ST is determined. In the following step 103, the course P is generated so that the vehicle V stops in the stop adaptation area ST. Next, the routine proceeds to step 105. On the other hand, when the stop request of the vehicle V is not output, the process proceeds from step 101 to step 104, and the normal course P is generated. Next, the routine proceeds to step 105. In step 105, the movement control of the vehicle V is executed.

  FIG. 12 shows a routine for executing the stop request control of the first embodiment according to the present invention. This routine is repeatedly performed when the automatic operation control is to be performed. Referring to FIG. 12, in step 201, it is determined whether or not the driver is in a state in which manual driving cannot be performed. When the driver cannot perform the manual driving, the process then proceeds to step 202, where a request to stop the vehicle V is output. On the other hand, when the driver is not in a state in which manual driving cannot be performed, the processing cycle ends without outputting a request to stop the vehicle V.

  Next, a second embodiment according to the present invention will be described. The following mainly describes differences from the first embodiment according to the present invention.

  FIG. 13 is a block diagram of a moving object automatic operation control system according to a second embodiment of the present invention. Referring to FIG. 13, the electronic control unit 10 according to the second embodiment of the present invention includes a disaster information receiving unit 22. The disaster information receiving unit 22 is configured to receive disaster information via a communication network such as the Internet, for example. The disaster information is output together with information indicating a place where the disaster occurred when a disaster such as a fire, an earthquake, a tsunami or the like occurs.

  In the second embodiment according to the present invention, the stop request determination unit 13 outputs a stop request for the vehicle V when receiving disaster information on a disaster occurring within a certain distance from the current position of the vehicle V. On the other hand, when the disaster information is not received, or when the disaster location is far from the current position of the vehicle V even if the disaster information is received, the stop request of the vehicle V is not output.

  Also in the second embodiment according to the present invention, when a stop request for the vehicle V is output from the stop request determination unit 13, the stop adaptation area determination unit 14 performs the stop adaptation based on the environment map information in the environment map storage device 6. Determine the area. Next, the course generation unit 12c generates the course P such that the vehicle V stops in the stop adaptation area. Next, the movement control unit 12d controls the vehicle V so that the vehicle V moves along the course P.

  Also in the second embodiment according to the present invention, the path P is generated such that the vehicle V stops in the stop adaptation area ST closest to the current position of the vehicle V, while ensuring the safe and secure stop of the vehicle V.

  FIG. 14 shows a routine for executing the stop request control of the second embodiment according to the present invention. This routine is repeatedly performed when the automatic operation control is to be performed. Referring to FIG. 14, in step 201a, it is determined whether or not disaster information regarding a disaster that has occurred within a certain distance from the current position of the vehicle V has been received. When the disaster information is received, the process proceeds to step 202, where a request to stop the vehicle V is output. On the other hand, when the disaster information is not received, the processing cycle ends without outputting a request to stop the vehicle V.

  Next, a third embodiment according to the present invention will be described. The following mainly describes differences from the first embodiment according to the present invention.

  FIG. 16 is a block diagram of a moving object automatic operation control system according to a third embodiment of the present invention. Referring to FIG. 16, the electronic control unit 10 according to the third embodiment of the present invention includes a driver instruction input unit 23. The driver instruction input unit 23 is configured to input a vehicle stop instruction from the driver and an urgency of stopping the vehicle. That is, when the driver wants to automatically stop the vehicle V, the driver inputs the vehicle stop instruction and the urgency of the vehicle stop through the driver instruction input unit 23. To this end, the driver instruction input unit 23 includes, for example, a button, a dial, a touch panel, a voice recognition device (microphone), and the like. In the third embodiment according to the present invention, the urgency of stopping the vehicle is input in a form that changes continuously or stepwise.

  Also in the third embodiment according to the present invention, in the first region in which the state quantity representative value is smaller than the predetermined setting representative value and the state quantity variability is lower than the predetermined setting variability, the state quantity representative value is smaller. An area adjacent to the second area whose value is larger than the set representative value and whose state quantity variability is lower than the set variability is determined as the stop adaptation area. In the third embodiment according to the present invention, the set variability is further set based on the urgency of stopping the vehicle. Specifically, when the urgency of stopping the vehicle is high, the setting variability is set higher than when the urgency of stopping the vehicle is low. With this configuration, the number of the first regions can be increased when the urgency of stopping the vehicle is high compared to when the urgency of stopping the vehicle is low. May increase. Therefore, when the urgency of stopping the vehicle is high, the stop adaptation region can be found relatively easily, and therefore, the vehicle V can be stopped relatively quickly.

That is, in the example shown in FIG. 16, when the driver inputs the vehicle stop instruction and the urgency of the vehicle stop, and when the input urgency of the vehicle stop is low, the determined stop adaptation region is only the region STZ. Then, the course PZ is generated so that the vehicle V stops in the stop adaptation area STZ. If a vehicle stop instruction and a vehicle stop urgency are input from the driver and the input vehicle stop urgency is medium, the determined stop adaptation area is assumed to be the areas STZ and STY. the currently most the near stop-fit region STY from the position of the vehicle V is selected, course PY is generated such that the vehicle V is stopped at stop-fit region STY. When a vehicle stop instruction and a vehicle stop urgency are input from the driver, and when the input vehicle stop urgency is high, the determined stop adaptation regions are assumed to be regions STZ, STY, and STX. , The stop adaptation area STX closest to the current position of the vehicle V is selected, and the route PX is generated so that the vehicle V stops in the stop adaptation area STX. In this manner, the vehicle V is automatically stopped at a location along the driver's desire.

  In another embodiment (not shown), when the urgency of stopping the vehicle is low, an area where the state quantity representative value is smaller than the set representative value and the state quantity variability is relatively lower than the first set variability is lower. When the urgency of stopping the vehicle is set to the first area and the state quantity representative value is smaller than the set representative value and the state quantity changeability is relatively high and the second set changeability is lower than the first set changeability, the first area is set to the first area. Area.

  FIG. 17 shows a routine for executing the stop request control of the third embodiment according to the present invention. This routine is repeatedly performed when the automatic operation control is to be performed. Referring to FIG. 17, in step 201b, it is determined whether or not a vehicle stop instruction has been input from the driver. When a vehicle stop instruction is input, the process then proceeds to step 202, where a request to stop the vehicle V is output. On the other hand, when the vehicle stop instruction has not been input, the processing cycle ends without outputting a request to stop the vehicle V.

  The embodiments according to the invention which have just been described can also be combined with one another. In one example, the electronic control unit 10 includes at least two of a driver status sensor 21, a disaster information receiving unit 22, and a driver instruction input unit 23.

  Further, in another embodiment (not shown) according to the present invention, in the first embodiment or the second embodiment according to the present invention, the setting variability is set based on the urgency of stopping the vehicle. Specifically, when the urgency of stopping the vehicle is high, the setting variability is set higher than when the urgency of stopping the vehicle is low. In this way, the vehicle V can be stopped quickly when the urgency of stopping the vehicle is high.

  In the embodiment according to the present invention described above, the acceleration or deceleration in the front-rear direction of the vehicle V is maintained within a certain range, and the acceleration or deceleration in the lateral direction of the vehicle V is maintained in a certain range. The stop adaptation region is selected to be maintained within. In another embodiment (not shown) according to the present invention, these acceleration / deceleration ranges are expanded when the urgency of stopping the vehicle is high compared to when the urgency of stopping the vehicle is low. As a result, when the urgency of stopping the vehicle is high, the vehicle V can be stopped in a closer stop adaptation region.

REFERENCE SIGNS LIST 1 external sensor 6 environment map storage device 10 electronic control unit 12 automatic operation control unit 12 c course generation unit 13 stop request determination unit 14 stop adaptation area determination unit 21 driver state sensor M environment map information

Claims (1)

An environmental map storage device that stores environmental map information and an electronic control unit, comprising:
The environmental map information includes:
Position information representing a plurality of positions in the space,
The state quantity representative value of each of the plurality of positions, the state quantity representative value associated with the corresponding position information,
The state quantity variability of each of the plurality of positions, the state quantity variability associated with the corresponding position information,
And the state quantity variability represents the easiness of change of the state quantity of the corresponding position with respect to time,
The electronic control unit includes:
Stop adaptation area determination that is configured to determine a stop adaptation area suitable for stopping the moving object based on the position information, the state quantity representative value, and the state quantity variability of the environmental map information. An automatic operation control system for a moving object, comprising a unit.

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