JP7718331B2 - Driving control system, driving control device, autonomous driving vehicle, driving control method, and driving control program - Google Patents

Description

This disclosure relates to driving control technology for controlling the driving of autonomous vehicles.

Patent Document 1 discloses a system for allowing unmanned vehicles to safely pass through automatic doors. This system is equipped with a control device that drives the automatic door when it receives a door-open request signal from the unmanned vehicle, and sends a door-full-open detection signal to the unmanned vehicle when it detects that the door is fully open.

Patent No. 2618251

The system in Patent Document 1 requires that the automatic door be equipped with a control device that controls the automatic door in response to a door-open request signal from the unmanned vehicle. Therefore, it may be difficult to pass through an automatic door that does not have such a control device. For these reasons, this system may have limited versatility.

An object of the present disclosure is to provide a cruise control system with improved versatility. Another object of the present disclosure is to provide a cruise control device with improved versatility. Yet another object of the present disclosure is to provide an autonomous vehicle with improved versatility. Yet another object of the present disclosure is to provide a cruise control method with improved versatility. Yet another object of the present disclosure is to provide a cruise control program with improved versatility.

The technical means of the present disclosure for solving the problems will be explained below. Note that the reference symbols in parentheses in the claims and this section indicate the correspondence with the specific means described in the embodiments described in detail below, and do not limit the technical scope of the present disclosure.

A first aspect of the present disclosure is a driving control system having a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, the system comprising:
The processor
driving an autonomous vehicle toward a closed automatic door;
Learning door map data that associates the sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
is configured to execute

A second aspect of the present disclosure is a driving control device having a processor (102), configured to be mountable on an autonomous vehicle (1), and configured to control driving of the autonomous vehicle passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor
driving an autonomous vehicle toward a closed automatic door;
Learning door map data that associates the sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
is configured to execute

A third aspect of the present disclosure is an autonomous vehicle having a processor (102) and passing through an automatic door (AD) that is controlled from a closed state to an open state in response to an approach of a moving object,
The processor
Running towards a closed automatic door;
Learning door map data that associates the sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
is configured to execute

A fourth aspect of the present disclosure is a driving control method executed by a processor (102) to control driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, the method comprising:
driving an autonomous vehicle toward a closed automatic door;
Learning door map data that associates the sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
Includes.

A fifth aspect of the present disclosure provides a travel control program stored in a storage medium (101) and including instructions to be executed by a processor (102) for controlling travel of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, the program comprising:
The command is,
driving an autonomous vehicle toward a closed automatic door;
The door map data is learned by associating the sensing results of the door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and the door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with the position related information of the automatic door.
Includes.

In these first to fifth aspects, door map data that associates the sensing results of the automatic door's door opening distance and door opening time with the automatic door's position-related information is learned as the autonomous vehicle travels. Therefore, it may be possible to control passing through each automatic door based on the door map data. Because this learning is possible through control on the autonomous vehicle side, it may be unnecessary to install a device on the automatic door side to control it in response to signals from the autonomous vehicle. This may improve versatility.

A sixth aspect of the present disclosure is a driving control system having a processor (102) and controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to an approach of a moving object,
The processor
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
driving the vehicle at a speed that correlates with the door opening distance and the door opening time indicated by the door map data with respect to the closed automatic door;
is configured to execute

According to a seventh aspect of the present disclosure, there is provided a driving control device having a processor (102), configured to be mountable on an autonomous vehicle (1), and configured to control driving of the autonomous vehicle passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, the driving control device comprising:
The processor
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
driving the vehicle at a speed that correlates with the door opening distance and the door opening time indicated by the door map data with respect to the closed automatic door;
is configured to execute

According to an eighth aspect of the present disclosure, there is provided an autonomous vehicle having a processor (102) and passing through an automatic door (AD) that is controlled from a closed state to an open state in response to an approach of a moving object, the autonomous vehicle comprising:
The processor
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
Traveling at a speed that correlates with the door opening distance and door opening time represented by the door map data with respect to the closed automatic door;
is configured to execute

According to a ninth aspect of the present disclosure, there is provided a driving control method executed by a processor (102) to control driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, the method comprising:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
driving the vehicle at a speed that correlates with the door opening distance and the door opening time indicated by the door map data with respect to the closed automatic door;
Includes.

According to a tenth aspect of the present disclosure, there is provided a travel control program stored in a storage medium (101) and including instructions to be executed by a processor (102) for controlling travel of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, the program comprising:
The command is,
Storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information about the automatic door;
driving the vehicle at a speed that correlates with the door opening distance and the door opening time indicated by the door map data with respect to the closed automatic door;
Includes.

The sixth to tenth aspects allow the vehicle to travel at a speed that correlates with the door opening distance and door opening time, based on door map data that associates the sensing results of the automatic door's door opening distance and door opening time with the automatic door's position-related information. This eliminates the need for the automatic door to provide a device for controlling the automatic door in response to signals between the autonomous vehicle and the automatic door. This improves versatility.

1 is a block diagram showing the overall configuration of an embodiment; FIG. 1 is a schematic diagram illustrating an autonomous vehicle to which an embodiment is applied. 1 is a block diagram showing a functional configuration of a cruise control system according to an embodiment; FIG. 10 is a diagram showing a series of driving operations of an autonomous vehicle when learning is successful. FIG. 10 is a diagram illustrating a series of driving operations of an autonomous vehicle when learning fails. 4 is a flowchart illustrating a travel control flow according to one embodiment. 4 is a flowchart illustrating a travel control flow according to one embodiment.

One embodiment of the present disclosure is described below with reference to the drawings.

(First embodiment)
An autonomous driving control system 100 of a first embodiment shown in Fig. 1 controls the driving of an autonomous driving vehicle 1 shown in Fig. 2. The autonomous driving vehicle 1 is, for example, a transport robot that provides a transport service by transporting luggage while traveling on roads. The operation of the autonomous driving vehicle 1 is managed by communication with an external center. The autonomous driving vehicle 1 may also be a logistics robot that transports luggage in a warehouse where the luggage is stored.

The autonomous vehicle 1 comprises a body 2 having an internal space for storing luggage, and a plurality of running wheels 3 provided on the body 2. The autonomous vehicle 1 is a running body that runs using a battery 5 built into the body 2 as a power source.

The autonomous vehicle 1 is equipped with a sensor system 10, a communication system 20, a map database (hereinafter referred to as "DB") 30, an information presentation system 40, and a motor control unit 50, all of which are shown in Figure 3. The sensor system 10 acquires sensor information that can be used by the autonomous driving control system 100 by detecting the external and internal environments of the autonomous vehicle 1. To this end, the sensor system 10 is configured to include an external sensor 11 and an internal sensor 12.

The external sensor 11 acquires external information usable by the autonomous driving control system 100 from the external environment surrounding the autonomous vehicle 1. The external sensor 11 may acquire external information by detecting targets present in the external world of the autonomous vehicle 1. The target detection type external sensor 11 includes, for example, an optical sensor 11a such as a camera or LiDAR (Light Detection and Ranging / Laser Imaging Detection and Ranging), and a sonar 11b. The target detection type external sensor 11 may also include radar. The external sensor 11 may also include a contact sensor 11c that detects contact with surrounding objects.

The external sensor 11 may include a positioning type sensor that acquires external information by receiving positioning signals from GNSS (Global Navigation Satellite System) satellites that exist in the external world of the autonomous vehicle 1. An example of a positioning type external sensor 11 is a GNSS receiver 11d.

The internal sensor 12 acquires internal information usable by the autonomous driving control system 100 from the internal environment of the autonomous vehicle 1. The internal sensor 12 may acquire internal information by detecting specific physical quantities of motion within the internal environment of the autonomous vehicle 1. The internal sensor 12 of the physical quantity detection type is at least one of the following types: a driving speed sensor, an acceleration sensor, a gyro sensor, etc.

The communication system 20 acquires communication information usable by the autonomous driving control system 100 via wireless communication. The communication system 20 may send and receive communication signals between the autonomous vehicle 1 and a V2X system existing in the external world. The V2X type communication system 20 is, for example, at least one of a DSRC (Dedicated Short Range Communications) communication device and a cellular V2X (C-V2X) communication device. The V2X type communication system 20 can also be considered a sensor that acquires external information through communication. The V2X type communication system 20 enables the autonomous vehicle 1 to communicate with an external center.

Map DB 30 stores map information that can be used by autonomous driving control system 100. Map DB 30 stores at least map information covering the service area in which transportation services are provided by driving control system 100. Map DB 30 is configured to include at least one type of non-transitory tangible storage medium, such as semiconductor memory, magnetic media, or optical media. Map DB 30 may be a database of a locator that estimates the autonomous vehicle 1's own state quantities, including its own position. Map DB 30 may also be a database of a planning unit that plans the autonomous vehicle 1's travel. Map DB 30 may be configured from a combination of multiple types of these databases, etc.

The map DB 30 acquires and stores the latest map information, for example, by communicating with an external center via a V2X type communication system 20. Here, the map information is converted into two-dimensional or three-dimensional data representing the driving environment of the autonomous vehicle 1. In particular, it is preferable to use high-precision digital map data as three-dimensional map data.

The map information includes location-related information relating to the location of automatic doors AD within the service area. Here, automatic doors AD are doors that are controlled to open when a moving object is detected approaching, and controlled to close when it is detected that the moving object has left. The location-related information is information including the location of the automatic door AD or information associated with that location. For example, the location-related information is associated with the location of the automatic door AD and includes an identification ID assigned to each individual automatic door AD.

Map information may include road information that represents at least one of the following: the position, shape, and road surface condition of the road itself. Map information may also include marking information that represents at least one of the following: the position and shape of signs and road markings attached to the road. Map information may also include structure information that represents at least one of the following: the position and shape of buildings and traffic lights facing the road.

The information presentation system 40 presents alarm information to people in the vicinity of the autonomous vehicle 1. The information presentation system 40 may include a visual presentation unit that presents alarm information by stimulating the vision of people in the vicinity. The visual presentation unit may include, for example, at least one type of monitor device that stimulates the vision by displaying a video or image, and a light-emitting unit that stimulates the vision by emitting a lamp. The information presentation system 40 may also include an auditory presentation unit that presents alarm information by stimulating the hearing of the occupant. The auditory presentation unit may be, for example, at least one type of speaker, buzzer, vibration unit, etc.

The motor control unit 50 is a control unit that controls the drive motors that rotate the running wheels 3. A motor control unit 50 is provided for at least one pair of left and right running wheels 3, and controls the supply of electricity to the drive motors based on a control command (current command value) from the autonomous driving control system 100.

The autonomous driving control system 100 is connected to the onboard components of the autonomous driving vehicle via at least one of, for example, a LAN (Local Area Network) line, a wire harness, an internal bus, or a wireless communication line. The autonomous driving control system 100 is configured to include at least one dedicated computer.

The dedicated computer that constitutes the cruise control system 100 may be a planning ECU (Electronic Control Unit) that plans a target trajectory for the autonomous vehicle 1 to travel. The dedicated computer that constitutes the cruise control system 100 may be a trajectory control ECU that causes the actual trajectory to follow the target trajectory for the autonomous vehicle 1. The dedicated computer that constitutes the cruise control system 100 may be an actuator ECU that controls each electric actuator of the autonomous vehicle 1.

The dedicated computer that constitutes the cruise control system 100 may be a sensing ECU that controls the sensor system 10 of the autonomous vehicle 1. The dedicated computer that constitutes the cruise control system 100 may be a locator ECU that estimates the autonomous vehicle 1's state quantities, including its own position, based on a map database. The dedicated computer that constitutes the cruise control system 100 may be an information presentation ECU that controls the autonomous vehicle 1's information presentation system 40. The dedicated computer that constitutes the cruise control system 100 may be a computer (center, etc.) outside the vehicle body 2 that constitutes, for example, a center or mobile terminal that can communicate via the communication system 20.

The dedicated computer that constitutes the cruise control system 100 has at least one memory 101 and one processor 102. The memory 101 is at least one type of non-transitory tangible storage medium, such as semiconductor memory, magnetic media, or optical media, that non-temporarily stores computer-readable programs and data. Here, "storage" may refer to accumulation in which data is retained even when the autonomous vehicle 1 is turned off, or temporary storage in which data is erased when the autonomous vehicle 1 is turned off. The processor 102 includes at least one type of core, such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), RISC (Reduced Instruction Set Computer)-CPU, DFP (Data Flow Processor), or GSP (Graph Streaming Processor).

In the cruise control system 100, the processor 102 executes multiple instructions contained in a cruise control program stored in the memory 101 to control the cruise of the autonomous vehicle 1. In this way, the cruise control system 100 constructs multiple functional blocks for controlling the cruise of the autonomous vehicle 1. The multiple functional blocks constructed in the cruise control system 100 include a recognition block 110, a cruise block 120, a data processing block 130, and a learning block 140, as shown in FIG. 3.

The driving control method in which driving control system 100 controls the driving of autonomous vehicle 1 through the cooperation of these blocks 100, 120, 130, and 140 is executed according to the driving control flow shown in Figures 6 and 7. This driving control flow will be described below in accordance with Figures 6 and 7, with reference to Figures 4 and 5. This driving control flow is executed repeatedly while autonomous vehicle 1 is running, particularly while driving to the destination. Note that each "S" in this driving control flow represents multiple steps executed by multiple commands included in the driving control program.

First, in S10 of Figure 6, the recognition block 110 determines whether it has recognized the automatic door AD that is the target of passage. For example, the recognition block 110 may determine whether it has recognized the automatic door AD based on external information from the external sensor 11. The processing of S10 is repeated while the autonomous vehicle 1 is traveling at normal speed V until the automatic door AD is recognized. Note that the recognition distance of the automatic door AD by the external sensor 11 is assumed to be greater than the moving object detection distance of a typical automatic door AD.

Once an automatic door AD is recognized, the flow proceeds to S20. In S20, the learning block 140 determines whether the automatic door AD is an unlearned automatic door AD for which door map data has not been learned. For example, the learning block 140 may determine that the automatic door AD is unlearned if there is no door map data whose location information substantially matches that of the automatic door AD.

If it is determined that the recognized automatic door AD has been learned rather than unlearned, the flow proceeds to S30. In S30, the learning block 140 determines whether the update conditions for updating the door map data for that automatic door AD are met.

The update condition is met, for example, when the margin of safety at the time of past passage based on the door map data from the previous learning exceeds a threshold. The margin of safety is a parameter that correlates with the distance between the automatic door AD and the autonomous vehicle 1 at the time of passage. The larger the distance, the greater the margin of safety.

Alternatively, the update condition may be a condition that is met when the number of failed passes based on the door map data from the previous learning exceeds an allowable number. Alternatively, the update condition may be a condition that is met when the difference between the door opening time from the previous learning and the door opening time T1 recognized during a previous pass after the previous learning is outside an allowable range. Alternatively, the update condition may be a condition that is met when one or more of the above-mentioned conditions are met as sub-conditions.

If it is determined that the update conditions are met, the flow proceeds to S70, described below. On the other hand, if it is determined that the update conditions are not met, the flow proceeds to S40. In S40, the travel block 120 sets an upper speed limit V2 for passing through the automatic door AD based on the door map data from the previous learning.

More specifically, the driving block 120 sets an upper limit speed V2 that correlates with the door opening distance D1 and door opening time T1 in the door map data. For example, the driving block 120 may set the upper limit speed V2 to the value obtained by dividing the door opening distance D1 by the door opening time T1, as shown in equation (1). Note that the upper limit speed V2 may also be a value obtained by multiplying the value obtained by dividing the door opening distance D1 by the door opening time T1 by a coefficient less than 1 as a safety factor.

If the automatic door AD has already been passed through since learning, the travel block 120 may use the upper limit speed V2 set the previous time the automatic door AD was passed through as the upper limit speed V2 for this time.

Then, in S45, the travel block 120 performs travel through the automatic door AD based on the upper limit speed V2. The travel block 120 determines a passing speed V3 based on the upper limit speed V2 and the detection results of nearby pedestrians, etc., and performs travel through at the determined passing speed V3. For example, if no moving object is detected in the vicinity, the travel block 120 sets the passing speed V3 to the upper limit speed V2, and if a moving object is detected, the travel block 120 sets the passing speed V3 to a speed lower than the upper limit speed V2.

Next, in S50, the traveling block 120 determines whether or not the autonomous vehicle 1 will be able to pass through the automatic door AD at the passing speed V3. If the traveling block 120 determines, based on external environment information from the external environment sensor 11, that the automatic door AD will open to an opening width that will allow the autonomous vehicle 1 to pass through before passing through the automatic door AD, the traveling block 120 determines that the passage was successful and continues traveling. As an example, the traveling block 120 determines that the passage will be unsuccessful if the following mathematical formula (1) is true:

In formula (2), d(t) is the remaining distance to the automatic door AD at the current time t. Furthermore, V _dr (t) is the opening speed of the automatic door AD at the current time t. W is the width of the autonomous vehicle 1. Formula (1) holds when the time it takes for the autonomous vehicle 1 to reach the automatic door AD is shorter than the time it takes for the automatic door AD to open beyond the width of the autonomous vehicle 1, resulting in a failure to pass through.

If it is determined that the passage has failed, the flow proceeds to S60. In S60, the traveling block 120 stops within the door opening distance D1, waits until the opening width of the automatic door AD exceeds the width of the moving body, and then performs the passing travel.

Then, in S65, the traveling block 120 reduces the passing speed V3 for the next passage. The traveling block 120 stores and retains this reduced passing speed V3 in a storage medium such as memory 101. Once the passage is complete, this flow ends and normal traveling control continues.

On the other hand, if the learning block 140 determines in S20 that the automatic door AD is an unlearned one for which door map data has not been learned, the flow proceeds to S70. In S70, the driving block 120 stops the autonomous vehicle 1 from driving. That is, through the series of processes in S10, S20, and S70, the autonomous vehicle 1 will temporarily stop when it approaches an unlearned automatic door AD close enough to be recognized.

Next, in S80, the recognition block 110 calculates the distance from the autonomous vehicle 1 to the automatic door AD based on the external environment information as the initial distance D0. The recognition block 110 stores the calculated initial distance D0 in the memory 101.

Then, in S90, the recognition block 110 determines whether a moving obstacle MO has been detected in the vicinity of the autonomous vehicle 1 and automatic door AD based on external information, etc. A moving obstacle MO is a moving object such as a pedestrian or another autonomous vehicle 1. If it is determined that a moving obstacle MO has been detected, the block waits until the moving obstacle MO has moved away from the vicinity of the autonomous vehicle 1 and automatic door AD and is no longer detected. If it is determined that a moving obstacle MO has not been detected, the flow proceeds to S100.

In S100, the recognition block 110 determines whether the automatic door AD is closed based on external information. If it is determined that the door is not closed, the recognition block 110 waits until it is closed. If it is determined that the door is closed, the flow proceeds to S110.

If the automatic door AD does not close after waiting for a predetermined period of time, the recognition block 110 may determine that the autonomous vehicle 1 has already entered the moving object detection range of the automatic door AD, and the travel block 120 may execute a process to retreat until the automatic door AD closes. Alternatively, if the automatic door AD does not close after waiting for a predetermined period of time, the travel block 120 may execute a process to pass through the automatic door AD at a predetermined speed.

In S110, the travel block 120 starts travel of the autonomous vehicle 1 toward the closed automatic door AD. At this time, the travel block 120 performs travel control at a learning speed V1. The learning speed V1 is the travel speed during learning that is pre-stored in the memory 101, etc. The learning speed V1 is set to a speed lower than the average human walking speed (e.g., approximately 1 km/h). For example, the average human walking speed is set to 4.4 km/h, which is the average of walking speeds by gender and age described in "The Chemistry of Walking" by Kunio Akutsu. Alternatively, the average human walking speed may be set to 5.8 km/h, which is defined as the human walking speed in JIS B9715:2013 or ISO 13855:2010. Alternatively, the learning speed V1 may be a speed lower than the average walking speed of pedestrians around the automatic door AD detected by the external sensor 11.

Next, in S120 of Figure 7, the recognition block 110 determines when the automatic door AD begins to open. That is, the recognition block 110 repeatedly detects the opening operation of the automatic door AD in a predetermined detection cycle, and when it detects an opening operation, it sets that detection timing as the opening start timing. When the opening start timing is detected, the flow proceeds to S130.

In S130, the recognition block 110 determines whether a target has been detected in the detection judgment area A1 between the automatic door AD and the autonomous vehicle 1. Specifically, the recognition block 110 determines whether a moving obstacle MO has been detected in the direction of the automatic door AD based on the detection judgment area A1. The recognition block 110 determines that a moving object entering the detection judgment area A1 set between the autonomous vehicle 1 and the automatic door AD, as shown in FIG. 5, is a moving obstacle MO in the direction of the automatic door AD. Note that while the detection judgment area A1 in FIG. 5 is set in front of the autonomous vehicle 1, the detection judgment area A1 may also be set to include the sides and rear of the autonomous vehicle 1. Furthermore, if a moving object behind the automatic door AD can be detected, the detection judgment area A1 may also be set to include the area behind the automatic door AD.

If it is determined that a moving obstacle MO has been detected, the flow proceeds to S140. In S140, the travel block 120 stops the autonomous vehicle 1. In the following S150, the travel block 120 backs up the autonomous vehicle 1 to a point that is the initial distance D0 from the automatic door AD. After S150, the flow returns to S90 in Figure 6.

On the other hand, if it is determined in S130 that a moving obstacle MO has not been detected, the flow proceeds to S160. In S160, the traveling block 120 stops the autonomous vehicle 1. Through the series of processes in S120, S130, and S160, the autonomous vehicle 1 is stopped at substantially the same time as the automatic door AD begins to open upon detection of the autonomous vehicle 1 by the automatic door AD.

Next, in S170, the learning block 140 associates the door opening distance D1, which is the distance from the stop position to the automatic door AD, with the identification ID of the automatic door AD and stores it in memory 101. Alternatively, or in addition, the learning block 140 may associate the door opening distance D1 with the identification ID and transmit it to the center. The door opening distance D1 is detected as a sensing result by, for example, the external sensor 11.

Next, in S180, the learning block 140 counts up a timer for measuring the door open time T1 as a sensing result. After the count-up, in S190, the recognition block 110 determines whether the timing has come for the autonomous vehicle 1 to pass through the automatic door AD. For example, the recognition block 110 determines that the timing has come when the opening width of the automatic door AD falls within the allowable passage range. The allowable passage range is the range in which the opening width is equal to or greater than a threshold value.

This threshold value may be determined according to the width of the opening when the automatic door AD is opened to a position where it does not come into contact with the autonomous vehicle 1. Such a threshold value may be determined according to the structure of the automatic door AD, the route R and dimensions of the autonomous vehicle 1. To elaborate on the dimensions, if the automatic door AD is a door that opens horizontally, the threshold value is determined according to the width dimension of the autonomous vehicle 1. Alternatively, if the automatic door AD is a door that opens vertically, the threshold value is determined according to the height dimension of the autonomous vehicle 1.

As an example, if the automatic door AD is a sliding door on both sides as shown in Figures 4 and 5, and the passage route R is specified to pass through the center position between the doors, the threshold value may be determined in accordance with the vehicle width as described above. On the other hand, if the passage route R is specified to pass through a position offset from the center position between the doors, the threshold value may be determined in accordance with the amount of offset from the center position in addition to the vehicle width.

Alternatively, this threshold value may be the opening width (full opening width) when the automatic door AD is fully open.

If it is determined in S190 that it is not time to pass, the flow returns to S180 and the timer continues counting up.

On the other hand, if it is determined that the time to pass has arrived, the flow proceeds to S200. In S200, the learning block 140 associates the door open time T1, which is the time from when the door starts to open until when it is possible to pass, with the identification ID of the automatic door AD and stores it in memory 101. Alternatively, or in addition, the learning block 140 may associate the door open time T1 with the identification ID and transmit it to the center.

Then, in S210, the learning block 140 initializes the timer. Then, in S220, the driving block 120 controls the driving of the autonomous vehicle 1 so that it passes through the automatic door AD, which has already reached the passable timing, at an initial passing speed V0. The initial passing speed V0 is set to, for example, a speed equal to or greater than the learning speed V1. After S220, this flow ends and transitions to normal driving control.

According to the first embodiment described above, door map data that associates the sensing results of the door opening distance D1 and door opening time T1 of the automatic door AD with the position-related information of the automatic door AD is learned as the autonomous vehicle 1 travels. Therefore, it may be possible to control passing through each automatic door AD based on the door map data. Because this learning is possible through control on the autonomous vehicle 1 side, it may be unnecessary to install a device on the automatic door AD side to perform control in response to signals from the autonomous vehicle 1. This may improve versatility.

(Other embodiments)
Although one embodiment has been described above, the present disclosure should not be construed as being limited to the embodiment described above, and can be applied to various embodiments within the scope that does not deviate from the gist of the present disclosure.

In a modified example, the dedicated computer that constitutes the driving control system 100 may have at least one of a digital circuit and an analog circuit as its processor. Here, a digital circuit is at least one of the following: an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), an SOC (System on a Chip), a PGA (Programmable Gate Array), and a CPLD (Complex Programmable Logic Device). These digital circuits may also have memory that stores programs.

In addition to the embodiments and variations described above, the above-described embodiments and variations may be implemented in the form of a processing circuit (e.g., a processing ECU, etc.) or a semiconductor device (e.g., a semiconductor chip, etc.) as a control device that is configured to be mountable on a host vehicle and has at least one processor 102 and one memory 101.

(Additional Note)
This specification discloses the following technical ideas and combinations thereof.

(Technical thought 1)
A driving control system having a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
a cruise control system configured to perform the above steps.

(Technical thought 2)
Learning the door map data includes:
The driving control system according to Technical Idea 1 includes storing the door map data in a storage medium (101).

(Technical thought 3)
Learning the door map data includes:
The driving control system according to Technical Idea 1 or Technical Idea 2 includes transmitting the door map data to a center outside the autonomous vehicle.

(Technical thought 4)
Driving the autonomous vehicle includes:
driving the automatic door for which the door map data has not been learned;
The automatic door, which has learned the door map data, is driven at a speed that correlates with the door opening distance and the door opening time represented by the door map data.
A cruise control system according to any one of Technical Ideas 1 to 3, including:

(Technical Thought 5)
Driving the autonomous vehicle includes:
A driving control system according to any one of technical ideas 1 to 4, which includes stopping driving in accordance with the timing at which the automatic door for which the door map data has not yet been learned starts to open.

(Technical Thought 6)
Driving the autonomous vehicle includes:
When a target is detected in a detection determination area (A1) between the automatic door for which the door map data has not been learned and the autonomous vehicle, the autonomous vehicle is moved backward to a closed position where the automatic door is in the closed state.
Re-running the automatic door from the closed position;
Including,
Learning the door map data includes:
interrupting learning of the door map data upon detection of the target;
Resuming the learning by re-driving;
A cruise control system according to any one of Technical Ideas 1 to 5, including:

(Technical Thought 7)
Driving the autonomous vehicle includes:
A driving control system according to any one of technical ideas 1 to 6, which includes driving the automatic door for which the door map data has not been learned at a speed lower than an average human walking speed.

(Technical Thought 8)
A driving control system having a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
a cruise control system configured to perform the above steps.

(Technical Thought 9)
A driving control device having a processor (102), configured to be mountable on an autonomous vehicle (1), and configured to control driving of the autonomous vehicle passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
A cruise control device configured to perform the above.

(Technical Thought 10)
A driving control device having a processor (102), configured to be mountable on an autonomous vehicle (1), and configured to control driving of the autonomous vehicle passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
A cruise control device configured to perform the above.

(Technical Thought 11)
An autonomous vehicle having a processor (102) that passes through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
Traveling toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
1. An autonomous vehicle configured to perform the

(Technical Thought 12)
An autonomous vehicle having a processor (102) that passes through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
Traveling at a speed correlated with the door opening distance and the door opening time represented by the door map data with respect to the automatic door in a closed state;
1. An autonomous vehicle configured to perform the

(Technical Thought 13)
A driving control method executed by a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, comprising:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
A driving control method including:

(Technical Thought 14)
A driving control method executed by a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, comprising:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
A driving control method including:

(Technical Thought 15)
A travel control program stored in a storage medium (101) and including instructions to be executed by a processor (102) for controlling travel of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The instruction:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates the sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information of the automatic door;
A driving control program including:

(Technical Thought 16)
A travel control program stored in a storage medium (101) and including instructions to be executed by a processor (102) for controlling travel of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The instruction:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information about the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
A driving control program including:

1: Autonomous vehicle, 100: Driving control system, 101: Memory (storage medium), 102: Processor, AD: Automatic door, A1: Detection and judgment area, C: Center, D1: Door opening distance, T1: Door opening time

Claims (16)

A driving control system having a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
a cruise control system configured to perform the above steps. Learning the door map data includes:
2. The cruise control system of claim 1, further comprising storing the door map data in a storage medium (101). Learning the door map data includes:
The cruise control system according to claim 1 , further comprising transmitting the door map data to a center outside the autonomous vehicle. Driving the autonomous vehicle includes:
driving the automatic door for which the door map data has not been learned;
driving the automatic door, for which the door map data has been learned, at a speed that correlates with the door opening distance and the door opening time represented by the door map data;
The cruise control system of claim 1 , comprising: Driving the autonomous vehicle includes:
2. The driving control system according to claim 1, further comprising: stopping driving of the automatic door in accordance with the timing at which the automatic door for which the door map data has not yet been learned starts to open. Driving the autonomous vehicle includes:
When a target is detected in a detection determination area (A1) between the automatic door for which the door map data has not been learned and the autonomous vehicle, the autonomous vehicle is moved backward to a closed position where the automatic door is in the closed state.
Re-running the automatic door from the closed position;
Including,
Learning the door map data includes:
interrupting learning of the door map data upon detection of the target;
Resuming the learning by re-driving;
The cruise control system of claim 1 , comprising: Driving the autonomous vehicle includes:
2. The driving control system according to claim 1, further comprising causing the vehicle to travel at a speed equal to or slower than an average human walking speed in relation to the automatic door for which the door map data has not yet been learned. A driving control system having a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
a cruise control system configured to perform the above steps. A driving control device having a processor (102), configured to be mountable on an autonomous vehicle (1), and configured to control driving of the autonomous vehicle passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
A cruise control device configured to perform the above. A driving control device having a processor (102), configured to be mountable on an autonomous vehicle (1), and configured to control driving of the autonomous vehicle passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
A cruise control device configured to perform the above. An autonomous vehicle having a processor (102) that passes through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
Traveling toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
1. An autonomous vehicle configured to perform the An autonomous vehicle having a processor (102) that passes through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The processor:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
Traveling at a speed correlated with the door opening distance and the door opening time represented by the door map data with respect to the automatic door in a closed state;
1. An autonomous vehicle configured to perform the A driving control method executed by a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, comprising:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
A driving control method including: A driving control method executed by a processor (102) for controlling driving of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object, comprising:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information of the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
A driving control method including: A travel control program stored in a storage medium (101) and including instructions to be executed by a processor (102) for controlling travel of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The instruction:
driving the autonomous vehicle toward the automatic door in a closed state;
learning door map data that associates the sensing results of a door opening distance (D1), which is the distance to the automatic door when the automatic door starts to open, and a door opening time (T1), which is the time from the opening start time to the passable time when the autonomous vehicle can pass, with position-related information of the automatic door;
A driving control program including: A travel control program stored in a storage medium (101) and including instructions to be executed by a processor (102) for controlling travel of an autonomous vehicle (1) passing through an automatic door (AD) that is controlled from a closed state to an open state in response to the approach of a moving object,
The instruction:
storing door map data in a storage medium (101) that associates sensing results of a door opening distance (D1), which is the distance to the automatic door at the timing when the automatic door starts to open, and a door opening time (T1), which is the time from the timing when the automatic door starts to open until the timing when the autonomous vehicle can pass, with position-related information about the automatic door;
driving the automatic door in a closed state at a speed correlated with the door opening distance and the door opening time represented by the door map data;
A driving control program including: