JP7267383B1 - Vehicle control device and vehicle control method - Google Patents

Abstract

A vehicle control device capable of executing automatic driving control with high reachability to a destination is provided. A vehicle control device according to the present disclosure includes an ambient environment information acquisition unit 202, a positioning unit 204 that measures the position of a vehicle, a map information acquisition unit 201, a positioning error estimation unit 206 that estimates a positioning error, An action planning unit 209 that generates an action plan, an action planning unit 210 that generates an action plan, and first map information that determines that the map information can be used for the action plan when the positioning error is less than the action plan threshold a determination unit 207; a second map information determination unit 208 that determines that the map information can be used for the action plan when the positioning error is less than the action plan threshold, which is smaller than the action plan threshold; and a vehicle control unit 211 for controlling the own vehicle to follow the target locus and the target vehicle speed when it is determined that the map information can be used. [Selection drawing] Fig. 1

Description

The present application relates to a vehicle control device and a vehicle control method.

Vehicle control devices have been proposed for realizing automatic driving of vehicles. In particular, in automatic driving toward a destination set by the user, a driving behavior that the own vehicle should execute is planned (hereinafter also referred to as an action plan), and a target trajectory and target vehicle speed are planned (hereinafter referred to as an action plan) to realize the action plan. , also referred to as an operation plan), and then controls actuators such as steering, accelerator, and brake (hereinafter also referred to as vehicle control) so that the vehicle follows the target based on the operation plan.

There is an automatic driving system that measures the position of the vehicle with a positioning satellite and utilizes map information around the position of the vehicle in order to implement an action plan or to make information used for operation planning and vehicle control redundant.

However, positioning by positioning satellites can include relatively large positioning errors. Furthermore, the map information to be referred to may differ from the actual road environment because the positioning error increases depending on the radio wave condition and the reliability of the map information decreases. Also, when the error included in the map information is large, it becomes necessary to stop the automatic driving system. If the automatic driving system stops unnecessarily, the convenience of the automatic driving system will be impaired. Furthermore, when the automated driving system stops, it is necessary to transfer driving authority to the driver.

In order to solve the above-mentioned problems, it is necessary to decide whether map information can be used for automatic driving control and whether to continue the operation of the automatic driving system, depending on the accuracy of the map itself or the accuracy of the self-position measured by positioning satellites. Appropriate judgments, etc. must be made.

As a vehicle control technology that solves such a problem, for example, Patent Document 1 discloses a vehicle control device that changes the control mode of automatic driving control according to the situation of mismatch between map information and information detected by an in-vehicle sensor. disclosed.

Further, Patent Document 2 discloses a driving support device that determines whether autonomous driving control of the own vehicle is possible depending on whether the estimation error of the self-position at the point ahead on the planned travel route is within the allowable error. disclosed.

JP 2019-20782 A Japanese Patent Application Laid-Open No. 2021-6431

The vehicle control device described in Patent Document 1 transfers the driving authority to the driver by changing the method of recognizing obstacles or decelerating the vehicle according to the matching state between the on-vehicle sensor and the map information. It can be implemented smoothly. Further, in the driving support device described in Patent Literature 2, the permissible error of the position of the vehicle is increased as the position becomes farther from the vehicle, thereby preventing the automatic driving control from stopping unnecessarily.

However, since it does not determine the conditions under which the map information cannot be used for each of the action plan, operation plan, and vehicle control, automatic driving control is stopped even under conditions where the action plan can be executed. It is possible that you will lose it. As a result, it becomes impossible to execute the driving action necessary for traveling on the travel route, and the vehicle may deviate from the original travel route and fail to reach the target point.

The present disclosure has been made in order to solve the above problems, and it is possible to determine whether or not map information can be used appropriately based on positioning errors for each of action planning, motion planning, and vehicle control. A vehicle control device and a vehicle control method that improve reachability to a target point by continuing automatic operation control when map information can be used in an action plan even in a situation where map information cannot be used in the action plan. intended to provide

The vehicle control device disclosed in the present application includes:
a surrounding environment information acquisition unit that acquires surrounding environment information of the own vehicle;
a positioning unit that measures the position of the vehicle based on signals transmitted from positioning satellites;
a map information acquisition unit that acquires map information on a route traveled by the own vehicle;
a positioning error estimating unit for estimating a positioning error of the vehicle position;
an action planning unit that generates an action plan that sets a route for the own vehicle to reach a target point and actions on the route;
a motion planning unit that generates a motion plan that sets a target trajectory and a target vehicle speed that are used to execute the motion plan;
a first map information determination unit that determines that the map information can be used for the action plan when the positioning error is less than the action plan threshold;
a second map information determination unit that determines that the map information can be used for the action plan when the positioning error is less than the action plan threshold, which is smaller than the action plan threshold;
If it is determined that the map information can be used for the action plan and the action plan, controlling the own vehicle to follow the target locus and the target vehicle speed, and applying the map information to the action plan. a vehicle control unit that controls the own vehicle based on the own vehicle position and the surrounding environment information when it is determined that the vehicle cannot be used;
Prepare.

The vehicle control method disclosed in the present application comprises:
A vehicle control method in which the following steps are executed by a processing circuit,
a surrounding environment information obtaining step of obtaining surrounding environment information of the own vehicle;
a positioning step of positioning the vehicle position based on a signal transmitted from a positioning satellite;
a map information acquisition step of acquiring map information on a route traveled by the own vehicle;
a positioning error estimation step of estimating a positioning error of the vehicle position;
an action plan step of generating an action plan that sets a route for the own vehicle to reach a target point and actions on the route;
a motion planning step of generating a motion plan for setting a target trajectory and a target vehicle speed used to execute the motion plan;
a first map information determining step of determining that the map information can be used for the action plan if the positioning error is less than the action plan threshold;
a second map information determining step of determining that the map information can be used for the action plan if the positioning error is less than the action plan threshold, which is smaller than the action plan threshold;
If it is determined that the map information can be used for the action plan and the action plan, controlling the own vehicle to follow the target locus and the target vehicle speed, and applying the map information to the action plan. a vehicle control step of controlling the own vehicle based on the own vehicle position and the surrounding environment information when it is determined that the vehicle cannot be used;
including.

According to the vehicle control device and the vehicle control method according to the present application, it is determined based on the positioning error whether or not the map information can be appropriately used for each of the action plan, the motion plan, and the vehicle control. Even in situations where map information cannot be used, the map information is used to generate the action plan, and automatic driving control is continued to prevent the vehicle from deviating from the target route and to reach the target point. There is an effect that a vehicle control device and a vehicle control method that can improve reachability are obtained.

Objects, features, aspects, and advantages of the technology disclosed herein will become more apparent from the detailed description and accompanying drawings set forth below.

1 is a functional block diagram showing the configuration of a vehicle control device according to Embodiment 1; FIG. 1 is a schematic diagram of a vehicle equipped with a vehicle control device according to Embodiment 1; FIG. 2 is a functional block diagram showing a hardware configuration for realizing the vehicle control device according to Embodiment 1; FIG. FIG. 4 is a schematic diagram showing a setting example of a target trajectory based on an action plan for reaching a target point and a setting example of an action execution point based on the action plan in the vehicle control device according to Embodiment 1; It is a schematic diagram which shows the example which cannot change a lane at an action execution point, deviates from a target locus|trajectory, and cannot reach|attain a target point by interruption of automatic driving|operation. FIG. 2 is a flowchart showing a vehicle control method according to Embodiment 1; FIG.

Embodiments will be described below with reference to the attached drawings. It should be noted that the drawings are shown schematically, and for the convenience of explanation, the configuration may be omitted or simplified as appropriate. In addition, the mutual relationship of sizes and positions of configurations shown in different drawings is not necessarily described accurately and can be changed as appropriate.

In addition, in the description given below, the same components are denoted by the same reference numerals, and their names and functions are also the same. Therefore, a detailed description thereof may be omitted to avoid duplication.

Also, in the descriptions set forth below, specific positions and orientations such as "top", "bottom", "left", "right", "side", "bottom", "front" or "back" are used. Even if the meaning terms are used, these terms are used for convenience in order to facilitate understanding of the contents of the embodiments, and have nothing to do with the direction of actual implementation. It does not.

In addition, even if ordinal numbers such as "first" or "second" are used in the description below, these terms are used to facilitate understanding of the contents of the embodiments. These ordinal numbers are used for convenience and are not limited to the order or the like that can occur with these ordinal numbers.

Embodiment 1.
<Configuration of Vehicle Control Device>
FIG. 1 is a functional block diagram showing the configuration of a vehicle control device 100 according to Embodiment 1. As shown in FIG. The vehicle control device 100 includes a map information acquisition unit 201, a surrounding environment information acquisition unit 202, a vehicle state quantity acquisition unit 203, a positioning unit 204, a running locus estimation unit 205, a positioning error estimation unit 206, a first map information determination unit 207, A second map information determination unit 208 , an action planning unit 209 , an operation planning unit 210 and a vehicle control unit 211 are provided.

The action planning unit 209 prepares an action plan for setting a route (also referred to as a target route) for the vehicle to reach the target point and actions to be executed such as changing lanes and turning left or right at an intersection necessary for traveling on the target route. A motion plan for setting a target trajectory and a target vehicle speed for executing the action plan is generated by the motion planning unit 210, and a target steering required to follow the target trajectory and the target vehicle speed is generated by the vehicle control unit 211. Amount and target acceleration/deceleration are calculated. By instructing the target steering amount and the target acceleration/deceleration from the vehicle control device 100 to the actuator 212, the vehicle 1 is automatically controlled. Based on the magnitude of the positioning error Φ of the vehicle position, it is determined whether map information is to be used when generating the action plan and motion plan. The target trajectory means a route with high positional accuracy necessary for the vehicle to travel along the target route, for example, within the driving lane.
Each configuration of the vehicle control device according to Embodiment 1 will be described below.

The map information acquisition unit 201 acquires travel route and map node data from the navigation device 122 .

The surrounding environment information acquisition unit 202 acquires surrounding environment information such as lane markings detected by a group of sensors such as the front camera 111 and the radar sensor 112, distances between the vehicle and features, and surrounding targets.

Vehicle state quantity acquisition unit 203 acquires outputs from a group of sensors such as steering angle sensor 131 , gyro sensor 133 , vehicle speed sensor 134 , acceleration sensor 135 . That is, the vehicle state quantity acquisition unit 203 acquires vehicle state quantities necessary for detecting the running state of the own vehicle from the sensor group.

The positioning unit 204 has a function of positioning the own vehicle position based on the output from a GNSS (Global Navigation Satellite System) sensor 121 . That is, the positioning unit 204 measures the position of the vehicle based on signals transmitted from positioning satellites. It also has a function of interpolating the position of the own vehicle by estimating the travel locus of the own vehicle based on the output from the travel locus estimation unit 205 when satellite positioning is interrupted.

The travel locus estimation unit 205 estimates the travel locus of the own vehicle based on the surrounding environment information acquired from the surrounding environment information acquisition unit 202 or the vehicle state quantity acquired from the vehicle state quantity acquisition unit 203 .

The estimation of the running trajectory of the own vehicle using the surrounding environment information output by the surrounding environment information acquisition unit 202 can be performed, for example, by comparing the lane marking detection result of the front camera 111 and the lane marking information included in the map node data, Alternatively, by comparing road edge information such as side walls and guardrails from the radar sensor 112 with road edge information included in the map node data, the travel locus of the host vehicle is estimated.

For estimating the travel locus based on the vehicle state quantity output by the vehicle state quantity acquisition unit 203, for example, from detection data such as the steering angle sensor 131, the gyro sensor 133, the vehicle speed sensor 134, and the acceleration sensor 135, the yaw rate, By obtaining the forward speed and the like and calculating the amount of movement of the own vehicle using a Kalman filter or the like, it is possible to estimate the running trajectory of the own vehicle.

The travel locus estimated by the travel locus estimation unit 205 is output to the positioning unit 204, and the vehicle position is interpolated when the satellite positioning reliability Rsg of the GNSS sensor 121 is lower than a predetermined value.

The positioning error estimating unit 206 uses the travel route and map information output by the map information acquiring unit 201, the surrounding environment information output by the surrounding environment information acquiring unit 202, the vehicle position output by the positioning unit 204, and the travel trajectory estimating unit 205. A positioning error Φ of the own vehicle position is estimated based on the output estimated running trajectory of the own vehicle.

The first map information determination unit 207 determines whether the map information can be used by the action planning unit 209 according to the magnitude of the positioning error Φ estimated by the positioning error estimation unit 206 .

The second map information determination unit 208 determines whether the map information can be used by the operation planning unit 210 according to the magnitude of the positioning error Φ estimated by the positioning error estimation unit 206 .

The action plan unit 209 obtains the travel route output from the map information acquisition unit 201, the map information determined to be usable for the action plan by the first map information determination unit 207, and the self-positioned vehicle determined by the positioning unit 204. Execution actions such as changing lanes, turning right or left at intersections, merging, and diverging for the vehicle to follow the target route based on the vehicle position, and action execution points consisting of action execution points and action execution grace distances. set. The execution action and action execution points for the host vehicle to travel along the target route are collectively called an action plan. In other words, the action plan means setting the route and actions on the route for the vehicle to reach the target point.

The map information mainly used in the action plan includes the absolute position at each node included in the map node data, that is, information such as latitude, longitude and altitude, section type, number of lanes, curvature, vehicle speed limit information, etc. information.

The action planning unit 210 uses the map information determined to be usable by the second map information determining unit 208, the vehicle position measured by the positioning unit 204, the action to be performed and the action execution point calculated by the action planning unit 209, and the surrounding area. A target trajectory and a target vehicle speed are set based on the surrounding environment information acquired by the environment information acquisition unit 202 . As for the method of calculating the target trajectory and the target vehicle speed, there are various known methods such as complementary curve application, graph search, sample base, and numerical optimization, and any method may be applied. In other words, the action plan is to set the target trajectory and target vehicle speed required to execute the action plan.

The map information mainly used in motion planning includes the absolute position at each node included in the map node data, that is, latitude, longitude and altitude information, lane width, cant angle or inclination angle information, peripheral This includes information on features and the like.

The vehicle control unit 211 calculates a target steering amount and a target acceleration/deceleration for following the target trajectory and target vehicle speed set by the motion planning unit 210 . The calculation of the target steering amount and the target acceleration/deceleration can be performed by a known calculation method such as a calculation method based on feedback control or a calculation method based on MPC (Model Predictive Control).

The actuator 212 includes an electric power steering (EPS) unit 5 , a powertrain unit 6 , a brake unit 7 , an EPS controller 310 , a powertrain controller 320 and a brake controller 330 . The actuator 212 controls the EPS, the brake, and the accelerator so that the vehicle 1 follows the target steering amount and target acceleration/deceleration.

<Configuration of vehicle including vehicle control device>
A vehicle 1 equipped with a vehicle control device 100 according to Embodiment 1 will be described below. FIG. 2 is a system configuration diagram showing a schematic configuration of the vehicle 1 equipped with the vehicle control device 100 according to the first embodiment. 2, a vehicle 1 includes a steering wheel 2, a steering shaft 3, a steering unit 4, an EPS unit 5, a powertrain unit 6, a brake unit 7, a front camera 111, a radar sensor 112, and a GNSS. A sensor 121, a navigation device 122, a steering angle sensor 131, a steering torque sensor 132, a gyro sensor 133, a vehicle speed sensor 134, an acceleration sensor 135, a vehicle control device 100, an EPS controller 310, and a power train controller. 320 and a brake controller 330 .

A steering wheel 2 (hereinafter also referred to as steering wheel) installed for the driver to operate the vehicle 1 is coupled to a steering shaft 3 . A steering unit 4 is connected to the steering shaft 3 . The steering unit 4 rotatably supports front wheels as steered wheels, and is steerably supported by the body frame.

The torque generated by the operation of the steering wheel 2 by the driver rotates the steering shaft 3, and the steering unit 4 steers the front wheels left and right. This allows the driver to control the amount of lateral movement of the vehicle 1 when the vehicle 1 moves forward and backward. The steering shaft 3 can also be rotated by the EPS unit 5. By instructing the EPS controller 310, the front wheels can be freely steered independently of the operation of the steering wheel 2 by the driver. .

The vehicle control device 100 is composed of an integrated circuit such as a microprocessor, and includes an A/D conversion circuit, a D/A conversion circuit, a CPU (Central Processing Unit), a ROM (Read only Memory), and a RAM (Random Access Memory). etc. The vehicle control device 100 includes a front camera 111, a radar sensor 112, a GNSS sensor 121, a navigation device 122, a steering angle sensor 131, a steering torque sensor 132, a gyro sensor 133, a vehicle speed sensor 134, an acceleration sensor 135, and an EPS controller 310. A power train controller 320 and a brake controller 330 are connected.

The vehicle control device 100 processes information input from various connected sensors according to a program stored in the ROM, transmits a target control amount to the EPS controller 310, and transmits a target driving force to the powertrain controller 320. and transmit the target braking force to the brake controller 330 .

The front camera 111 is installed at a position where the marking line in front of the vehicle 1 can be detected as an image, and detects information on surrounding objects in front of the vehicle 1, such as lane information and the position of obstacles, based on the image information. In the first embodiment, only the front camera for detecting the surrounding objects in front is taken as an example, but a camera for detecting the surrounding objects behind or on the side may be installed.

The radar sensor 112 is installed so that the front of the vehicle 1 can be detected. By irradiating a radar in front of the vehicle 1 and detecting the reflected wave of the radar, it is possible to detect dynamic targets such as other vehicles and static targets such as side walls existing around the vehicle 1. Outputs relative position and relative velocity.

In Embodiment 1, only the radar that detects the surrounding objects in front of the vehicle 1 was taken as an example, but a radar that detects the surrounding objects behind or to the sides of the vehicle 1 may be installed. Also, a LiDAR (Light Detection and Ranging) that detects an object by scanning measurement using a laser beam may be installed.

The GNSS sensor 121 receives radio waves, ie, signals, transmitted from positioning satellites with an antenna. Radio waves from terrestrial base stations such as RTK (Real Time Kinematic) may also be received together. The GNSS sensor 121 can obtain the absolute position (that is, latitude, longitude, and altitude), absolute orientation, and their reliability of the vehicle 1 by performing positioning calculations from these received radio waves.

In general, a GNSS sensor has a function of outputting a positioning quality in a positioning mode or a DOP (Dilution of Precision) that is the degree of influence of positioning satellite placement on a positioning error. Therefore, normally, the satellite positioning reliability Rsg of the output information is calculated based on the DOP.

The navigation device 122 has a function of calculating an optimum travel route for a target point set by the driver through the user interface, that is, a target route, and guides the vehicle 1 to the target point set by the driver. The navigation device 122 also records road information on the travel route. Here, the road information is map node data representing the shape of the route of the road. Each map node data includes absolute position (latitude, longitude and elevation), section type, number of lanes, lane width, cant angle or inclination angle information, curvature, vehicle speed limit information, surrounding features, etc. Information is included.

A steering angle sensor 131 detects the absolute angle of the steering wheel 2 . The steering torque sensor 132 detects torque applied to the steering shaft 3 . A gyro sensor 133 detects the yaw rate of the vehicle 1 . A vehicle speed sensor 134 detects the vehicle speed of the vehicle 1 . Acceleration sensor 135 detects the acceleration of vehicle 1 .

EPS controller 310 controls EPS unit 5 based on the target control amount transmitted from vehicle control device 100 . The EPS controller 310 can control, for example, the steering angle for the vehicle 1 to travel along the target trajectory.

Powertrain controller 320 controls powertrain unit 6 so as to achieve the target driving force transmitted from vehicle control device 100 . Further, when the driver performs speed control, the power train unit 6 is controlled based on the amount of depression of the accelerator pedal.

In the first embodiment, a vehicle having only an engine as a driving force source was taken as an example, but a vehicle having only an electric motor as a driving force source, or a vehicle having both an engine and an electric motor as driving force sources. and so on.

Brake controller 330 controls brake unit 7 so as to achieve the target braking force transmitted from vehicle control device 100 . Further, when the driver performs speed control, the brake unit 7 is controlled based on the amount of depression of the brake pedal.
The above is the description of the system configuration of the vehicle 1 including the vehicle control device 100 .

<Hardware Configuration of Vehicle Control Device>
FIG. 3 is a hardware configuration diagram of the vehicle control device 100. As shown in FIG. The vehicle control device 100 is an electronic control device for realizing automatic driving of the vehicle 1 . Each function of the vehicle control device 100 is implemented by a processing circuit included in the vehicle control device 100 . Specifically, the vehicle control device 100 includes, as processing circuits, an arithmetic processing unit 90 (computer) such as a CPU, a storage device 91 for exchanging data with the arithmetic processing unit 90, and an external signal input to the arithmetic processing unit 90. and an output circuit 93 for outputting a signal from the arithmetic processing unit 90 to the outside.

As the arithmetic processing unit 90, various logic circuits and various signal processing circuits such as ASIC (Application Specific Integrated Circuit), IC (Integrated Circuit), DSP (Digital Signal Processor), and FPGA (Field Programmable Gate Array) are provided. prepared Also good. Further, as the arithmetic processing unit 90, a plurality of units of the same type or different types may be provided, and each process may be shared and executed.

As the storage device 91, a RAM configured so that data can be read from and written to the arithmetic processing unit 90, a ROM configured so that data can be read from the arithmetic processing unit 90, and the like are provided. The storage device 91 includes non-volatile or volatile semiconductor memory such as flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), magnetic disk, flexible disk, optical disk, compact disk. , a mini disc, a DVD (Digital Versatile Disc), or the like may be used.

The input circuit 92 receives various sensors including output signals from the vehicle speed sensor 134, the gyro sensor 133, the steering angle sensor 131, the steering torque sensor 132, the acceleration sensor 135, the front camera 111, the radar sensor 112, the GNSS sensor 121, and the navigation device 122. , switches and communication lines are connected, and an A/D converter for inputting output signals of these sensors and switches and communication information to the arithmetic processing unit 90, a communication circuit, and the like are provided. Note that FIG. 3 illustrates only the vehicle speed sensor 134 among the sensors that output to the input circuit 92 .

The output circuit 93 includes a drive circuit and the like for outputting a control signal from the arithmetic processing unit 90 to a device including the power train unit 6 . The output circuit 93 outputs signals such as a target steering amount and a target acceleration/deceleration to the actuator 212 . Further, the arithmetic processing unit 90 can communicate with an external device (not shown) via the communication unit 99 .

Each function provided in the vehicle control device 100 is performed by the arithmetic processing device 90 executing software (program) stored in a storage device 91 such as a ROM, and executing the software (program) stored in the storage device 91, the input circuit 92 and the output circuit 93 of the vehicle control device 100. It is realized by cooperating with other hardware of Setting data such as threshold values and determination values used by the vehicle control device 100 are stored in a storage device 91 such as a ROM as a part of software (program).

Each function of the vehicle control device 100 may be configured by a software module, or may be configured by a combination of software and hardware.

When the arithmetic processing device 90 executes a program stored in an external memory or the like, the function of the vehicle control device 100 is to store an execution program stored in the storage device by a processing circuit in the RAM. It may be implemented by loading type software, firmware fixed in ROM, or a combination of both.

<Example of deviating from the target trajectory and not reaching the target point>
An example will be described in which the vehicle deviates from the target trajectory and cannot reach the target point due to suspension of automatic driving. FIG. 4 shows an example of setting the execution action and the action execution point according to the action plan, and an example of setting the target trajectory according to the action plan for reaching the target point according to the first embodiment. Further, FIG. 5 shows an example in which the vehicle cannot change lanes at the action execution point due to suspension of automatic driving, deviate from the target trajectory, and cannot reach the target point.

As shown in FIG. 4, when the vehicle is traveling in the right lane on a road with two lanes in each direction, if there is a target point ahead of the branch path from the left lane, the lane to the left lane before the branch point You will need to make a change and lane change to the diverted lane. In the action planning unit 209, using map information such as a map node or a distance to a branch point, an action to be taken and an action execution point for reaching the target point are set. That is, the action plan section 209 generates an action plan.

The motion planning unit 210 sets a target trajectory and a target vehicle speed for executing a target route composed of the execution action and the action execution points set by the action planning unit 209 and the action of the host vehicle on the target route, respectively. By controlling the vehicle control unit 211 so that the vehicle travels along the target locus, the vehicle can reach the target point. That is, the motion planning unit 210 generates a motion plan for setting the target trajectory and target vehicle speed.

As shown in FIG. 5, when the automatic driving is interrupted at a point before the planned action execution point due to the increase in the positioning error Φ, if the planned lane change cannot be executed at the action execution point, the host vehicle If the vehicle continues in the right lane and cannot enter the branch road, it may deviate from the set target trajectory and fail to reach the target point.

In the first embodiment, the case where there is a target point at the branch destination has been described. In addition, there is a similar problem in situations where the own vehicle cannot reach the target point.

In an example of FIG. 4, the action plan generated by the action plan unit 209, that is, the positioning error Φ allowed for the set execution action and the action execution point is the action plan generated by the action plan unit 210, That is, it is larger than the positioning error Φ that is allowed for the set target trajectory and target vehicle speed. That is, there is a relationship of positioning error permissible in the action plan>positioning error permissible in the action plan.

For example, in the action plan, the positioning error Φ in the lateral direction of the vehicle (perpendicular to the direction of travel of the vehicle), for which the use of map information is allowed, is In the case of part), it is sufficient if it is within the range where the lane can be discriminated. A typical positioning error Φ is ±1 m, ie on the order of 1 m. This means that the positioning error Φ allowed in the action plan is of the order of 1m.

In addition, for the vehicle speed plan based on the speed limit information on the driving route, or the target vehicle speed based on the road shape change (curvature, lane width, etc.) on the driving route (both are part of the action plan), the positioning error Φ is It is sufficient if the map information of the driving area is within a usable range. A typical positioning error Φ is ±10 m, ie of the order of 10 m. This means that the positioning error Φ allowed in the action plan is of the order of 10m.

On the other hand, the positioning error Φ in the lateral direction of the vehicle, which allows the use of map information in operation planning, must be within the allowable range for lane keeping control. A typical positioning error Φ is ±0.1 m, ie on the order of 0.1 m. This means that the positioning error Φ allowed in the motion plan is of the order of 0.1 m. That is, in the above specific example, the positioning error Φ allowed in the action plan is ten times the positioning error Φ allowed in the action plan.

Therefore, if the positioning error Φ that is permissible for the automatic driving control system is not set separately for the action plan and the motion plan, it is necessary to set the positioning error Φ that is permissible for both the action plan and the motion plan. In this case, it is necessary to match the required positioning error Φ with the allowable positioning error Φ for a stricter action plan. There is a risk of

In view of the above, in the vehicle control device and vehicle control method according to Embodiment 1, even in a situation where the positioning error Φ increases, each of the action plan, the operation plan, and the vehicle control is appropriately A vehicle control device and a vehicle control method that determine whether or not map information can be used and continue automatic driving control using map information in the action plan even in situations where the map information cannot be used in the action plan will be explained. .

<Vehicle control method>
FIG. 6 shows that in the vehicle control device 100 and the vehicle control method according to Embodiment 1, even when the positioning error Φ increases, the map information is appropriately applied to each of the action plan, the motion plan, and the vehicle control. It is a flowchart showing a vehicle control method for determining whether or not can be used, and using map information in the action plan to continue automatic driving control even in a situation where the map information cannot be used in the action plan.

First, in step S100, the positioning error estimator 206 estimates the positioning error Φ of the vehicle position. The information necessary for estimating the positioning error Φ includes the satellite positioning reliability Rsg of the GNSS sensor 121 acquired by the positioning unit 204, the map information of the travel point acquired by the map information acquisition unit 201, and the travel trajectory estimation unit 205. One or more of the estimated distance or estimated time of the estimated own vehicle running locus can be cited.

In the method using the satellite positioning reliability Rsg of the GNSS sensor 121, by evaluating the error range of the GNSS sensor 121 according to the reliability in advance, the positioning error Φ can be calculated from the satellite positioning reliability Rsg.

In the method using the map information of the driving point acquired by the map information acquisition unit 201, the GNSS sensor 121 detects road type information and features (for example, tunnels, underpasses, etc.) that have characteristics that cause an increase in positioning error Φ. The positioning error Φ can be calculated according to the traveling point, such as when traveling at a certain point.

In the method using the estimated distance or the estimated time of the vehicle travel trajectory, the travel trajectory estimation unit 205 interpolates the vehicle position by estimating the travel trajectory based on the vehicle state quantity output from the vehicle state quantity acquisition unit 203. In this state, the measurement error of the GNSS sensor 121 accumulates over time, and as a result, the error in the estimated value of the travel locus increases. Therefore, the positioning error Φ can be calculated according to the estimated distance or the length of the estimated time of the travel locus of the own vehicle.

Any one of the above methods may be used to estimate the positioning error Φ, or a plurality of methods may be used in combination. As an example of a combination of a plurality of methods, there is a method of taking the total value, average value, and maximum value of each positioning error Φ, but any method may be used.

In step S101, the first map information determination unit 207 determines whether or not the positioning error Φ of the map information is equal to or greater than the action plan threshold. The action plan threshold is an error value that is permissible for discriminating the driving lane. In other words, the action plan threshold is a boundary value that enables identification of the driving lane with respect to the positioning error Φ. If the positioning error Φ is greater than or equal to the action plan threshold value, that is, if Yes in step S101, step S108 is performed.If the positioning error Φ is less than the action plan threshold value, that is, if No in step S101, step S102 is performed. Execute.

In the action planning unit 209, the positioning error Φ necessary for using the map information such as the absolute position, section type, number of lanes, curvature, and vehicle speed limit information at each node included in the map node data is controlled to keep the lane. It is not necessary to have the positioning accuracy required for Therefore, by alleviating the positioning error Φ to an error value that is permissible for determining the driving lane, the action planning unit 209 can extend the duration of automatic driving.

In the above, an example of uniformly determining the applicability of the action plan to the map information has been shown. In addition to this example, a use determination threshold may be set individually for each piece of map information, and the execution range of the action plan may be changed according to the contents of the map information determined to be unusable. For example, a lane change plan is not possible, but a vehicle speed plan based on the vehicle speed limit on the travel route is possible.

In step S102, the second map information determination unit 208 determines whether or not the positioning error Φ is greater than or equal to the operation plan threshold value with respect to the map information. The operation planning threshold is set to a value equivalent to the accuracy required to keep the own vehicle running within the lane. That is, the operation planning threshold is a boundary value that allows the vehicle to maintain its travel within the travel lane with respect to the positioning error Φ. If the positioning error Φ is greater than or equal to the operation planning threshold, that is, if Yes in step S102, step S103 is executed. If the positioning error Φ is less than the operation planning threshold, that is, if No in step S102, step S107 is executed. .

In the operation planning unit 210, in order to use the map information such as the absolute position at each node, the lane width, the cant angle or inclination information, and the information of the surrounding features, which are included in the map node data, the lane keeping control is performed. Therefore, the allowable range of the positioning error Φ, which is separate from the action planning unit 209, is used to determine whether the map information can be used. can be judged appropriately.

In the case of Yes in step S102, in step S103, the action planning unit 209 uses the map information to set the execution action and action execution points for the own vehicle to travel along the target route, and execute step S104. do. In step S103, by using the map information for the action plan generated by the action planning unit 209, the lane change plan, intersection right/left turn plan, merging plan, branching plan, and It is possible to calculate the execution actions and action execution points necessary for realizing each plan, such as a vehicle speed plan based on vehicle speed limit information and a vehicle speed plan based on road shape changes (curvature, lane width, etc.) on the travel route. That is, it becomes possible for the action plan section 209 to generate an effective action plan.

In step S104, the motion planning unit 210 calculates the target trajectory and the target vehicle speed without using the map information, and executes step S105. In step S104, the action planning unit 209 uses the map information, while the action planning unit 210 does not use the map information. However, in principle, the accuracy of the target trajectory and target vehicle speed set by the motion planning unit 210 can be ensured. However, in step S105 to be described later, there may be a situation where the motion planning unit 210 determines that the accuracy of the target trajectory and the target vehicle speed cannot be ensured.

In step S105, it is determined whether or not information necessary for the operation planning unit 210 can be detected by a plurality of sensors mounted on the own vehicle. If the information necessary for the operation planning unit 210 can be detected by a plurality of sensors mounted on the own vehicle, that is, if Yes in step S105, step S107 is executed, and if the necessary information cannot be detected, that is, If No in step S105, step S106 is executed. The reason for providing step S105 is that, as a result of not using the map information for the motion planning in the motion planning unit 210, road markings, features, etc. necessary for calculating the target vehicle speed and the target route set by the motion planning are This is to confirm whether or not a redundant system for detecting surrounding environment information is not secured.

In step S106, the map information cannot be used for motion planning in the motion planning section 210, and the ambient environment information necessary for the motion planning section 210 is detected by the plurality of sensors in the ambient environment information acquisition section 202. Since the redundant system cannot be ensured for the first time, the automatic operation control is continued after prohibiting the driver's hands-off driving from the steering wheel. This is because information from only a single sensor may cause the vehicle to deviate from the lane or collide with a feature due to erroneous detection by the sensor.

In the above description of step S106, an example of changing the permission state of the driver's hands-free driving from the steering wheel when the sensor redundancy system is not ensured is shown. Alternatively, the automatic driving level may be changed (SAE LEVEL3→LEVEL2, SAE LEVEL2→LEVEL1).

In step S<b>107 , the automatic driving control is continued according to the action plan generated by the action planning section 209 and the action plan generated by the action planning section 210 . This is because when step S107 is executed after step S102, the positioning error Φ is smaller than both the action plan threshold and the action plan threshold, so the map information can be used for both the action plan and the action plan. Further, even when step S107 is executed after step S105, in the ambient environment information acquisition unit 202, if the information necessary for the motion planning unit 210 to generate a motion plan can be detected by one or more sensors, This is because it is possible to continue the automatic operation control as in the case of step S102. Note that, in step S107, the driver may be permitted to operate without the steering wheel.

In step S108, the action plan unit 209 does not generate an action plan, and the action plan unit 210 prepares an action plan based on the vehicle position measured by the positioning unit 204 and the surrounding environment information acquired by the surrounding environment information acquisition unit 202. It generates and continues the automatic operation control according to this operation plan.
The above is the description of the vehicle control method according to the first embodiment.

As described above, according to the vehicle control device 100 and the vehicle control method according to the first embodiment, even in a situation where the positioning error Φ increases, the map is displayed appropriately for each of the action plan, the operation plan, and the vehicle control. Determine whether the information can be used or not, and use the map information in the action plan even in situations where the map information cannot be used in the action plan. By continuing automatic driving control, the vehicle deviates from the target route. It is possible to obtain a vehicle control device and a vehicle control method that can prevent this and improve reachability to a target point.

Embodiment 2.
Vehicle control device 100 according to Embodiment 2 is characterized in that positioning error estimating section 206 performs the following operation. The configuration of the vehicle control device is the same as that of the vehicle control device 100 according to the first embodiment.

Positioning error estimator 206 in vehicle control device 100 according to Embodiment 2 estimates an increase or decrease in positioning error Φ based on road characteristic information included in map information. If the positioning error Φ increases due to the road characteristics and becomes equal to or greater than the road characteristics threshold, the first map information determination unit 207 determines that the map information cannot be used for the action plan.

When driving on roads with road characteristics where it is possible to know in advance that the positioning error Φ will increase, such as tunnels, underpasses, and between high-rise buildings, the positioning error can be reduced by estimating the increase in positioning error Φ in advance. This is because the estimation accuracy of Φ can be improved.

Embodiment 3.
Vehicle control device 100 according to Embodiment 3 is characterized in that positioning unit 204 performs the following operations. The configuration of the vehicle control device is the same as that of the vehicle control device 100 according to the first embodiment.

The positioning unit 204 in the vehicle control device 100 according to the third embodiment detects the vehicle state of the own vehicle acquired by the vehicle state quantity acquisition unit 203 when the signal transmitted from the positioning satellite is stopped and the satellite positioning is interrupted. Based on the state quantity, the trajectory estimator 205 estimates the trajectory of the vehicle, and uses the estimated trajectory to interpolate the vehicle position even when satellite positioning is interrupted.

The first map information determination unit 207 determines that the map information cannot be used for the action plan when the interpolation distance of the vehicle position is equal to or greater than the first interpolation threshold distance. Further, the second map information determination unit 208 determines that the map information cannot be used for the operation plan when the interpolation distance of the own vehicle position is equal to or greater than the second interpolation threshold distance. Note that the second interpolation threshold distance is set to a numerical value smaller than the first interpolation threshold distance.

Even if satellite positioning is interrupted and satellite positioning is not possible, positioning interpolation is possible by estimating the travel trajectory of the own vehicle from the vehicle state quantities such as vehicle speed and yaw rate acquired by the vehicle state quantity acquisition unit 203. Therefore, even while satellite positioning is interrupted, it is possible to extend the use of map information when generating an action plan and an action plan. However, as the distance or time for positioning interpolation (Dead Reckoning) increases, the positioning error increases due to accumulation of measurement errors included in the GNSS sensor 121 . Therefore, by setting the upper limit of the distance for performing positioning interpolation, it is possible to further improve the estimation accuracy of the positioning error.

<Modified Examples of Embodiments 1 to 3>
In the above embodiments, the dimensions, shapes, relative positional relationships, and implementation conditions of each component may be described, but these are examples in all aspects, and the present specification shall not be limited to those listed in

Accordingly, myriad modifications and equivalents not exemplified are contemplated within the scope of the technology disclosed herein. For example, when modifying, adding, or omitting at least one component, or when extracting at least one component of at least one embodiment and combining it with a component of another embodiment shall be included.

In addition, as long as there is no contradiction, "one" or "one or more" components may be provided in the embodiments described above.

Furthermore, each component in the embodiments described above is a conceptual unit, and within the scope of the technology disclosed in this specification, when one component is composed of a plurality of structures , the case where one component corresponds to a part of a structure, and further the case where a plurality of components are provided in one structure.

Further, each component in the embodiments described above includes structures having other structures or shapes as long as they exhibit the same function.

Also, the statements herein are referenced for all purposes relating to this technology and are not admitted to be prior art.

In addition, each component described in the embodiments described above is assumed to be software or firmware as well as hardware corresponding thereto, and in both concepts, each component is a "part". Or it is called a "processing circuit" or the like.

1 vehicle, 2 steering wheel, 3 steering shaft, 4 steering unit, 5 EPS unit, 6 power train unit, 7 brake unit, 100 vehicle control device, 201 map information acquisition unit, 202 ambient environment information acquisition unit, 203 vehicle state quantity acquisition unit, 204 positioning unit, 205 traveling locus estimation unit, 206 positioning error estimation unit, 207 first map information determination unit, 208 second map information determination unit, 209 action planning unit, 210 operation planning unit, 211 vehicle control unit, 212 actuator, 111 front camera, 112 radar sensor, 121 GNSS sensor, 122 navigation device, 131 steering angle sensor, 132 steering torque sensor, 133 gyro sensor, 134 vehicle speed sensor, 135 acceleration sensor, 310 EPS controller, 320 power train controller, 330 brake controller

Claims (14)

a surrounding environment information acquisition unit that acquires surrounding environment information of the own vehicle;
a positioning unit that measures the position of the vehicle based on signals transmitted from positioning satellites;
a map information acquisition unit that acquires map information on a route traveled by the own vehicle;
a positioning error estimating unit for estimating a positioning error of the vehicle position;
an action planning unit that generates an action plan that sets a route for the own vehicle to reach a target point and actions on the route;
a motion planning unit that generates a motion plan that sets a target trajectory and a target vehicle speed that are used to execute the motion plan;
a first map information determination unit that determines that the map information can be used for the action plan when the positioning error is less than the action plan threshold;
a second map information determination unit that determines that the map information can be used for the action plan when the positioning error is less than the action plan threshold, which is smaller than the action plan threshold;
If it is determined that the map information can be used for the action plan and the action plan, controlling the own vehicle to follow the target locus and the target vehicle speed, and applying the map information to the action plan. a vehicle control unit that controls the own vehicle based on the own vehicle position and the surrounding environment information when it is determined that the vehicle cannot be used;
A vehicle control device comprising: The vehicle control unit controls the own vehicle based on an operation plan that does not use the map information when the second map information determination unit determines that the positioning error is equal to or greater than the operation plan threshold. Item 1. The vehicle control device according to item 1. 3. The vehicle control device according to claim 1, wherein the action plan threshold value is a boundary value that enables identification of a driving lane with respect to the positioning error. 4. The vehicle according to any one of claims 1 to 3, wherein the operation plan threshold value is a boundary value that allows the vehicle to maintain running within the driving lane with respect to the positioning error. Control device. When the surrounding environment information to be used for the operation plan is secured in the surrounding environment information acquisition unit, automatic operation control is continued, and when the surrounding environment information to be used for the operation plan is not secured, from the driver's steering wheel 3. The vehicle control device according to claim 2, wherein the hands-free driving is prohibited. The positioning error estimator determines an increase or decrease in the positioning error based on the road characteristic information included in the map information, and if the positioning error based on the road characteristic information is equal to or greater than a road characteristic threshold, 2. The vehicle control device according to claim 1, wherein the determination unit further determines that the map information cannot be used in the action plan. a vehicle state quantity acquisition unit that acquires a vehicle state quantity of the own vehicle;
a travel trajectory estimation unit that estimates a travel trajectory of the own vehicle based on the vehicle state quantity of the own vehicle;
The positioning unit interpolates the vehicle position based on the estimated running trajectory when satellite positioning is interrupted,
the first map information determination unit further determines that the map information cannot be used for the action plan when the interpolation distance of the vehicle position is equal to or greater than a first interpolation threshold distance;
The second map information determination unit further determines that the map information cannot be used for the operation plan when the interpolation distance of the vehicle position is equal to or greater than a second interpolation threshold distance. Item 1. The vehicle control device according to item 1. 8. The vehicle control device according to claim 7, wherein the second interpolation threshold distance is set smaller than the first interpolation threshold distance. A vehicle control method in which the following steps are executed by a processing circuit,
a surrounding environment information obtaining step of obtaining surrounding environment information of the own vehicle;
a positioning step of positioning the vehicle position based on a signal transmitted from a positioning satellite;
a map information acquisition step of acquiring map information on a route traveled by the own vehicle;
a positioning error estimation step of estimating a positioning error of the vehicle position;
an action plan step of generating an action plan that sets a route for the own vehicle to reach a target point and actions on the route;
a motion planning step of generating a motion plan for setting a target trajectory and a target vehicle speed used for executing the motion plan;
a first map information determining step of determining that the map information can be used for the action plan if the positioning error is less than the action plan threshold;
a second map information determining step of determining that the map information can be used for the action plan if the positioning error is less than the action plan threshold, which is smaller than the action plan threshold;
If it is determined that the map information can be used for the action plan and the action plan, controlling the own vehicle to follow the target locus and the target vehicle speed, and applying the map information to the action plan. a vehicle control step of controlling the own vehicle based on the own vehicle position and the surrounding environment information when it is determined that the vehicle cannot be used;
vehicle control methods including; In the second map information determination step, if the positioning error is equal to or greater than the operation plan threshold, the vehicle control step controls the own vehicle based on an operation plan that does not use the map information. 10. A vehicle control method according to Item 9. 11. The vehicle control method according to claim 9, wherein the action plan threshold value is a boundary value that enables identification of a driving lane with respect to the positioning error. 12. The vehicle according to any one of claims 9 to 11, wherein the operation plan threshold value is a boundary value that allows the vehicle to maintain running in the lane with respect to the positioning error. control method. In the positioning error estimating step, an increase or decrease in the positioning error is determined based on the road characteristic information included in the map information, and if the positioning error based on the road characteristic information is equal to or greater than a road characteristic threshold, the first map information 10. The vehicle control method according to claim 9, wherein the determining step further determines that the map information cannot be used in the action plan. a vehicle state quantity obtaining step of obtaining a vehicle state quantity of the host vehicle;
a travel trajectory estimation step of estimating a travel trajectory of the own vehicle based on the vehicle state quantity of the own vehicle;
In the positioning step, when satellite positioning is interrupted, interpolating the vehicle position based on the estimated running trajectory;
In the first map information determining step, further determining that the map information cannot be used for the action plan when the interpolation distance of the vehicle position is equal to or greater than a first interpolation threshold distance;
In the second map information determining step, if the interpolation distance of the vehicle position is equal to or greater than a second interpolation threshold distance, further determining that the map information cannot be used for the operation plan;
10. The vehicle control method according to claim 9, wherein the second interpolation threshold distance is set smaller than the first interpolation threshold distance.

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