JP7515989B2 - Vehicle control device - Google Patents

Description

The present invention relates to a vehicle control device that controls a vehicle.

In recent years, research has been progressing on autonomous driving, which allows vehicles to run without user control.

Humans perform driving operations according to various situations, so the vehicle's acceleration, deceleration, and other movements are not uniform. In order to make the movements of an autonomous vehicle closer to those of a human driver, autonomous driving control is required to be similar to human driving operations.

International Publication No. 2018/230685

The objective of the present invention is to provide a vehicle control device that can perform control operations similar to those of a human driver.

To achieve the above object, a vehicle control device according to one aspect of the present invention includes a deceleration start means for starting deceleration of the vehicle at a predetermined deceleration rate for features present ahead of the vehicle, and a setting means for setting the predetermined deceleration rate according to the features.

With this configuration, when the vehicle starts to decelerate in response to a feature in the vehicle's path, the deceleration rate is set according to the feature. This allows the vehicle to be decelerated in a manner similar to human driving.

The setting means may acquire information about features from map information including information about roads and features, and set a predetermined deceleration for each feature identified from the acquired information.

In this configuration, for example, by updating map information, it is possible to set deceleration for each feature based on the latest feature information.

A vehicle control device according to another aspect of the present invention includes a creation means for creating an acceleration/deceleration curve showing the change in acceleration/deceleration in the section from the current position of the vehicle to the location of the feature, based on a deceleration corresponding to the feature, a target vehicle speed of the vehicle at the location of the feature, the current vehicle speed of the vehicle, and the legal speed or the maximum speed marked on a road sign in the section from the current position of the vehicle to the location of the feature, for a feature present ahead of the vehicle, and an acceleration/deceleration means for accelerating and decelerating the vehicle in accordance with the acceleration/deceleration curve created by the creation means.

With this configuration, the vehicle can be accelerated or decelerated depending on the features that exist in the vehicle's path. This allows the vehicle to be accelerated or decelerated in a manner similar to that of a human driver.

The setting means may acquire information about features from map information including information about roads and features, and create an acceleration/deceleration curve for each feature identified from the acquired information.

In this configuration, for example, by updating map information, acceleration/deceleration curves can be created for each feature based on the latest feature information.

The present invention allows control that closely resembles human driving operations when decelerating a vehicle.

1 is a block diagram showing an electrical configuration of a vehicle equipped with a collision avoidance control device according to an embodiment of the present invention; FIG. 2 is a block diagram showing a functional configuration of an autonomous driving ECU. 13 is a flowchart showing a flow of an acceleration/deceleration curve creation process. FIG. 13 is a diagram for explaining deceleration according to features; FIG. 2 is a diagram illustrating an example of a vehicle driving situation. FIG. 6 is a diagram showing acceleration/deceleration curves generated in the running conditions shown in FIG. 5 . FIG. 11 is a diagram showing another example of a vehicle traveling situation. FIG. 8 is a diagram showing acceleration/deceleration curves generated in the running conditions shown in FIG. 7 .

The following describes in detail an embodiment of the present invention with reference to the attached drawings.

<Vehicle configuration>
FIG. 1 is a block diagram showing the electrical configuration of a vehicle 1 equipped with a collision avoidance control device according to an embodiment of the present invention.

Vehicle 1 is equipped with an autonomous driving function and is capable of autonomous driving without user driving operations.

Vehicle 1 is equipped with multiple ECUs (Electronic Control Units) to control various parts. Each ECU has a microcontroller unit (microcomputer), which includes, for example, a CPU, a non-volatile memory such as a flash memory, and a volatile memory such as a dynamic random access memory (DRAM).

The multiple ECUs include a drive ECU 11, a steering ECU 12, a brake ECU 13, a meter ECU 14, and a body ECU 15. The drive ECU 11, the steering ECU 12, the brake ECU 13, the meter ECU 14, and the body ECU 15 are connected to enable communication according to a CAN (Controller Area Network) communication protocol, i.e., CAN communication.

The drive ECU 11 is a control unit that controls the drive device 21 of the vehicle 1. The drive device 21 may be configured to have an engine as a drive source, a motor as a drive source, or both an engine and a motor as drive sources. The drive device 21 includes a transmission that changes the speed of the drive force from the drive source and outputs it as necessary.

The steering ECU 12 is a control unit that controls the steering device 22 of the vehicle 1. The steering device 22 is, for example, an electric power steering device that applies the torque of an electric motor to a steering mechanism. The steering mechanism includes, for example, a rack-and-pinion steering gear, and is configured such that when the rack shaft moves in the vehicle width direction due to the torque of the electric motor, the left and right steered wheels turn left and right in accordance with the movement of the rack shaft.

The brake ECU 13 is a control unit that controls the braking device 23 of the vehicle 1. The braking device 23 may be hydraulic or electric. The hydraulic braking device 23 is equipped with a brake actuator, and the function of this brake actuator distributes hydraulic pressure to the wheel cylinders of the brakes provided on each wheel, and the hydraulic pressure applies braking force from each brake to the wheels, including the drive wheels.

The meter ECU 14 is a control unit that controls each part of the meter panel (not shown) of the vehicle 1. The meter panel is provided with instruments that display vehicle speed and engine RPM, as well as displays such as a liquid crystal display for displaying various information. In addition, an emergency stop switch 24 that is operated to issue an instruction to stop the automatic driving in an emergency is connected to the meter ECU 14.

The body ECU 15 is a control unit that controls various parts of the vehicle 1 that need to operate even when the ignition switch is off, such as the left and right turn signals and the door lock motors.

The multiple ECUs also include an autonomous driving ECU 31, a lidar ECU 32, and a monocular camera ECU 33 as control units for the autonomous driving function.

The automatic driving ECU 31 is the control center for automatic driving control. The automatic driving ECU 31 is connected to the drive ECU 11, steering ECU 12, brake ECU 13, meter ECU 14, and body ECU 15 so as to be able to communicate via CAN.

An omnidirectional lidar (LiDAR: Light Detection And Ranging) 34 is connected to the autonomous driving ECU 31, for example, via an Ethernet standard communication cable. The omnidirectional lidar 34 emits laser light in all directions 360°, receives reflected light from objects present within the search range with an optical sensor, and outputs a detection signal according to the reflected light. The detection signal from the omnidirectional lidar 34 is input to the autonomous driving ECU 31.

The automatic driving ECU 31 is also connected to a GPS receiver 35 via, for example, a USB (Universal Serial Bus) standard communication cable. The GPS receiver 35 is a receiver that receives positioning signals from GPS (Global Positioning System) satellites. The positioning signals received by the GPS receiver 35 are input from the GPS receiver 35 to the automatic driving ECU 31.

The LIDAR ECU 32 is connected to the autonomous driving ECU 31 so as to be able to communicate with it, for example, via an Ethernet standard communication cable. Six LIDARs 36 are connected to the LIDAR ECU 32. The LIDARs 36 irradiate a search range with laser light, receive reflected light from objects present within the search range with an optical sensor, and output a detection signal according to the reflected light. The LIDARs 36 are, for example, disposed at the left end, center, and right end of the front bumper of the vehicle 1, and the left end, center, and right end of the rear bumper. The detection signals output from each LIDAR 36 are input to the LIDAR ECU 32. The LIDAR ECU 32 processes the detection signals output from each LIDAR 36, and transmits the data obtained by the processing to the autonomous driving ECU 31.

The monocular camera ECU 33 is communicatively connected to the autonomous driving ECU 31 via, for example, a USB standard communication cable. A monocular camera 37 is connected to the monocular camera ECU 33. The monocular camera 37 is a camera that can continuously capture still images of the search range in front of the vehicle 1 at a predetermined frame rate. The monocular camera ECU 33 receives image signals of still images that are continuously output from the monocular camera 37. The monocular camera ECU 33 processes the image signals input from the monocular camera 37, and transmits the image data obtained by this processing to the autonomous driving ECU 31.

<Autonomous driving ECU>
FIG. 2 is a block diagram showing the functional configuration of the automatic driving ECU 31.

The autonomous driving ECU 31 includes an object recognition unit 41, a self-position estimation unit 42, a surrounding information integration unit 43, a route planning unit 44, and a vehicle control unit 45. These functional processing units are realized in software by program processing, or by hardware such as a logic circuit.

The object recognition unit 41 recognizes objects such as other vehicles and pedestrians around the vehicle 1 from information on the distance to the object (vehicle, pedestrian, building, curb, or other obstacle) obtained from the detection signal of the omnidirectional lidar 34 and from images captured by the monocular camera 37.

The self-position estimation unit 42 estimates the position (self-position) of the vehicle 1 by matching the point cloud data acquired from the detection signal of the omnidirectional lidar 34 with high-precision map data (point cloud data) 47, which is data of a high-precision map. The high-precision map is a high-precision three-dimensional map, and the high-precision map data 46 includes, for example, information such as the width and gradient of the road, and information on features such as dividing lines, shoulder lines, intersections, railroad crossings, stop lines, pedestrian crossings, and signs. The high-precision map data 46 may be stored in a non-volatile memory built into the microcomputer of the automatic driving ECU 31, or may be stored in a HDD (Hard Disk Drive) connected to the automatic driving ECU 31. The self-position estimation unit 42 also integrates the self-position estimated by matching the point cloud data with the self-position based on the positioning signal received by the GPS receiver 35 to improve the estimation accuracy of the self-position.

The surrounding information integration unit 43 receives as input the object recognition results by the object recognition unit 41, the self-position estimation results by the self-position estimation unit 42, and data obtained by processing the detection signals output from each LIDAR 36 by the LIDAR ECU 32 (see FIG. 1). High-precision map data 46 is also input to the surrounding information integration unit 43. The surrounding information integration unit 43 creates surrounding information integrated map data in which the vehicle 1, vehicles other than the vehicle 1, and objects such as pedestrians are arranged on a high-precision map. The surrounding information integration unit 43 then outputs the map information and object recognition information to an HMI (Human Machine Interface) device 47 such as a display arranged inside the vehicle 1.

The surrounding information integrated map data is input to the route planning unit 44 from the surrounding information integration unit 43. The route planning unit 44 plans a travel route to the destination of the vehicle 1 from the surrounding information integrated map data. The plan includes a target vehicle speed at each point on the travel route. The travel route plan also includes the setting of deceleration sections. The setting of deceleration sections will be described later. The route planning unit 44 then outputs the planned target vehicle speed and route data of the travel route including the deceleration sections to the HMI device 47.

The vehicle control unit 45 receives route data from the route planning unit 44. Based on the route data, the vehicle control unit 45 outputs commands to ECUs that control the operation of each part of the vehicle 1, such as the drive ECU 11, steering ECU 12, and brake ECU 13, so that the vehicle 1 travels along the travel route by automatic driving.

<Deceleration section setting>
Fig. 3 is a flowchart showing the flow of the deceleration section setting process Fig. 4 is a diagram for explaining deceleration according to features.

For example, after the destination of vehicle 1 is input on HMI device 47, an automatic driving start button displayed on HMI device 47 is pressed, and an instruction to start automatic driving is input from HMI device 47 to automatic driving ECU 31. When the instruction to start automatic driving is input to automatic driving ECU 31, a travel route to the destination of vehicle 1 is planned by route planning unit 44. The travel route is re-planned at a predetermined interval while vehicle 1 is traveling in automatic driving. Then, during automatic driving, vehicle 1 travels at each point on the travel route at the target vehicle speed for each point according to the most recently planned travel route. Automatic driving ends, for example, when vehicle 1 arrives at the destination or when emergency stop switch 24 is pressed and an instruction to stop automatic driving is input from meter ECU 14 to automatic driving ECU 31.

When planning and replanning a travel route, the route planning unit 44 performs the acceleration/deceleration curve creation process shown in FIG. 3.

In the acceleration/deceleration curve creation process, high-precision map data 46 included in the surrounding information integrated map data is used to search for features that exist on the travel route within a predetermined search range in the direction of travel from the current position of vehicle 1 and that require vehicle 1 to decelerate before it reaches that position, i.e., deceleration target features that are the target of deceleration for vehicle 1 (step S11).

The non-volatile memory built into the microcomputer of the autonomous driving ECU 31 stores the relationship between the deceleration target features included in the high-precision map data 46 and the deceleration of the vehicle 1 in front of the deceleration target features. The relationship between the deceleration target features and the deceleration is stored in the form of a table, for example, as a deceleration table.

The deceleration rate for each feature to be decelerated may be set for each feature to be decelerated, or may be set for each type of feature to be decelerated. When the deceleration rate is set for each feature to be decelerated, the deceleration rate for the feature to be decelerated may be set taking into consideration the characteristics of the area in which the feature to be decelerated is located (e.g., residential area, school zone, etc.). Information on the characteristics of the area is not included in the high-precision map data 46, so it may be stored in a non-volatile memory built into the microcomputer of the autonomous driving ECU 31, for example, and read out from the non-volatile memory, or it may be received from a server outside the vehicle 1 via the gateway ECU by data communication such as mobile wireless data communication.

Once the search for deceleration target features within the search range is completed, the deceleration is set for each deceleration target feature extracted by the search according to the deceleration table (step S12).

For each deceleration target feature or type of deceleration target feature, a target vehicle speed for the vehicle 1 at the location of the deceleration target feature is set so that the vehicle can safely pass through or stop at the location of the deceleration target feature. In the deceleration table, the deceleration target feature and the deceleration are associated so that the lower the target vehicle speed at the location of the deceleration target feature, the lower (smaller) the deceleration. For example, as shown in FIG. 4, for curves, points where the road width changes from large to small, and speed signs, it is not necessary to stop the vehicle 1 by decelerating only, so if the target vehicle speed is set to decrease in that order from the curve, the deceleration is set to decrease in that order. Also, for pedestrian crossings and stop lines, the target vehicle speed is set to 0, so a deceleration lower than the deceleration for the speed signs is set.

For each deceleration target feature, an acceleration/deceleration curve is created that indicates the change in acceleration/deceleration in the section from the current position of the vehicle 1 to the deceleration target feature based on the current speed of the vehicle 1, the legal speed or the maximum speed marked on the road sign in the section from the current position of the vehicle 1 to the deceleration target feature, the deceleration set according to the deceleration table, and the target vehicle speed of the vehicle 1 at the deceleration target feature (step S13). Then, based on the acceleration/deceleration curve for each deceleration target feature, the start point of the deceleration section for reducing the vehicle 1's speed at each deceleration target feature to the target vehicle speed is selected that is closest to the current position of the vehicle 1. Then, the drive device 21 and brake device 23 of the vehicle 1 are controlled via the drive ECU 11 and brake ECU 13 so that the vehicle 1 travels according to an acceleration/deceleration curve having a deceleration section whose start point is closest to the current position of the vehicle 1.

<Specific examples of automated driving control>
Fig. 5 is a diagram showing an example of a driving situation of the vehicle 1. Fig. 6 is a diagram showing acceleration/deceleration curves generated in the driving situation shown in Fig. 5.

For example, as shown in FIG. 5, assume that within a predetermined search range in the direction of travel from the current position of vehicle 1, a traffic light 51 is located 100 m away from the current position of vehicle 1, a pedestrian crossing 52 is located 200 m away from the current position, and the start of a curve 53 is located 250 m away from the current position.

In the deceleration zone setting process, a search is performed for deceleration target features within the search range. In the search under the above assumptions, a traffic light 51 100 m ahead of the current position of the vehicle 1, a pedestrian crossing 52 200 m ahead, and a curve 53 250 m ahead are identified as candidates for deceleration target features.

Then, the light (color) of the traffic light 51 is determined from the image captured by the monocular camera 37. If the green light (blue) of the traffic light 51 is on, the traffic light 51 (or the stop line provided for the traffic light) is determined not to be a deceleration target feature that is a target for decelerating the vehicle 1, and is excluded from the deceleration target features within the search range.

In addition, the detection signal from the omnidirectional lidar 34 is used to determine whether or not a pedestrian is present within a specified area that includes the crosswalk 52. If no pedestrian is present within the specified area, the crosswalk 52 (or the stop line in front of it) is determined not to be a feature subject to deceleration, and is excluded from the features subject to deceleration within the search range.

As a result, it is determined that the only deceleration target feature within the search range is curve 53, which is 250 m away from the current position of vehicle 1. Then, an acceleration/deceleration curve is created that shows the change in acceleration/deceleration in the section from the current position of vehicle 1 to the start of curve 53, based on the current speed of vehicle 1, the legal speed or the maximum speed indicated on road signs in the section from the current position of vehicle 1 to the start of curve 53, the deceleration set for curve 53 according to the deceleration table, and the target vehicle speed of vehicle 1 at the start of curve 53.

As shown in FIG. 6, the acceleration/deceleration curve is a graph in which the horizontal axis represents the distance from the current position of the vehicle 1 in the direction of travel and the vertical axis represents the vehicle speed of the vehicle 1, and the target vehicle speed at each position of the vehicle 1 is plotted. For example, in a section from the current position of the vehicle 1 up to about 25 m ahead, the vehicle 1 accelerates to a constant vehicle speed set to be lower than the legal speed or the maximum speed indicated on road signs, and in a section from about 25 m ahead to about 200 m ahead, the vehicle 1 travels at a constant vehicle speed, and in a section from about 200 m ahead to 250 m ahead where the vehicle approaches the curve 53, the acceleration/deceleration curve is created so that the vehicle 1 decelerates to the target vehicle speed at a deceleration rate according to the curve 53 in the deceleration section. Then, the drive device 21 and the brake device 23 of the vehicle 1 are controlled via the drive ECU 11 and the brake ECU 13 so that the vehicle 1 travels according to the acceleration/deceleration curve.

Figure 7 is a diagram showing another example of the driving condition of vehicle 1. Figure 8 is a diagram showing the acceleration/deceleration curves generated in the driving condition shown in Figure 7.

For example, if the light of traffic light 51 changes from green to red as shown in FIG. 7 while vehicle 1 is traveling according to the acceleration/deceleration curve shown in FIG. 6, traffic light 51 is added to the deceleration target features by the deceleration section setting process in the replanning of the travel route. Also, if the presence of a pedestrian is detected in a specified area including crosswalk 52, crosswalk 52 is added to the deceleration target features by the deceleration section setting process. As a result, the deceleration target features within a specified search range in the travel direction from the current position of vehicle 1 are determined to be traffic light 51 50 m away, crosswalk 52 150 m away, and curve 53 200 m away from the current position of vehicle 1.

As shown in FIG. 8, an acceleration/deceleration curve is set for each of the deceleration target features, that is, the traffic light 51, the crosswalk 52, and the curve 53. For the traffic light 51 with the red light on, as shown by the dashed line in FIG. 8, the acceleration/deceleration curve is created so that the vehicle 1 runs at a constant speed in a section from the current position of the vehicle 1 to about 30 m ahead, and the section from about 30 m ahead to the stop line provided for the traffic light 51 is set as a deceleration section, in which the vehicle 1 decelerates to the target vehicle speed of 0 km/h. For the crosswalk 52 where a pedestrian is present, as shown by the two-dot chain line in FIG. 8, the acceleration/deceleration curve is created so that the vehicle 1 runs at a constant speed in a section from the current position of the vehicle 1 to about 80 m ahead, and the section from about 80 m ahead to the stop line just before the crosswalk 52 is set as a deceleration section, in which the vehicle 1 decelerates to the target vehicle speed of 0 km/h. In addition, for curve 53, an acceleration/deceleration curve is created so that vehicle 1 travels at a constant speed in the section from vehicle 1's current position to approximately 150 m ahead, and the section from approximately 150 m ahead to 200 m ahead where curve 53 is approached is set as a deceleration section, in which vehicle 1 decelerates to the target vehicle speed at a deceleration rate according to curve 53.

After creating the acceleration/deceleration curves for each deceleration target feature, those acceleration/deceleration curves are referenced and the one whose deceleration section start point is closest to the current position of the vehicle 1 is selected. In the example shown in FIG. 8, the acceleration/deceleration curve created for the traffic light 51 is selected. Then, the drive device 21 and braking device 23 of the vehicle 1 are controlled via the drive ECU 11 and brake ECU 13 so that the vehicle 1 travels according to the acceleration/deceleration curve for that traffic light 51.

<Action and effect>
As described above, among features existing on the moving path of the vehicle 1 within a predetermined search range in the traveling direction from the current position of the vehicle 1, a deceleration target feature that requires the vehicle 1 to decelerate before the vehicle 1 reaches the position is searched for, and the deceleration of the vehicle 1 is set according to the deceleration target feature extracted by the search. Then, an acceleration/deceleration curve showing the change in acceleration/deceleration in the section from the current position of the vehicle 1 to the deceleration target feature is created based on the current speed of the vehicle 1, the legal speed or the maximum speed marked on the road sign in the section from the current position of the vehicle 1 to the deceleration target feature, the deceleration set according to the deceleration table, and the target vehicle speed of the vehicle 1 at the deceleration target feature, and when the vehicle 1 reaches the start point of the deceleration section according to the acceleration/deceleration curve, deceleration of the vehicle 1 is started. This allows control similar to human driving operation to be performed when decelerating the vehicle 1.

High-precision map data 46 is used to search for the deceleration target feature. Therefore, by updating the high-precision map data 46, it is possible to set the deceleration rate according to the deceleration target feature based on the latest feature information.

<Modification>
Although one embodiment of the present invention has been described above, the present invention can be embodied in other forms.

For example, in the above embodiment, an instruction to start autonomous driving is input from the HMI device 47 to the autonomous driving ECU 31, but an instruction to start autonomous driving may be input from a server outside the vehicle 1 to the autonomous driving ECU 31 via a gateway ECU by data communication such as mobile wireless data communication. Also, an instruction to start autonomous driving may be input to the autonomous driving ECU 31 when the vehicle 1 reaches an autonomous driving start point set on the travel route.

In addition, various design modifications may be made to the above-mentioned configuration within the scope of the claims.

1: Vehicle 11: Drive ECU (vehicle control device, deceleration start means, deceleration means)
13: Brake ECU (vehicle control device, deceleration start means, deceleration means)
31: Autonomous driving ECU (vehicle control device, setting means)
46: High-precision map data (map information)

Claims (1)

a generating means for generating an acceleration/deceleration curve showing changes in acceleration/deceleration in a section from the current position of the vehicle to the location of the feature, based on a deceleration corresponding to the feature, a target vehicle speed of the vehicle at the location of the feature, a current vehicle speed of the vehicle, and a legal speed or a maximum speed marked on a road sign in the section from the current position of the vehicle to the location of the feature;
an acceleration/deceleration means for accelerating and decelerating the vehicle in accordance with the acceleration/deceleration curve created by the creation means ,
A vehicle control device in which the deceleration according to the feature is set taking into consideration the characteristics of the area in which the feature is located .

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