Vehicle control devices

Abstract

The present invention relates to a vehicle control device. The vehicle control device selects a maximum number (Nx) of objects from a first object group (OB1) in descending order of priority as a second object group (OB2), and performs collision avoidance control when an index value indicating the likelihood of collision with an object included in the second object group satisfies a predetermined condition. The vehicle control device lowers the priority of specific objects when the vehicle speed (Vs) is below a predetermined speed threshold (Vth). Specific objects are objects that are considered to be moving at a slower speed than a four-wheeled vehicle.

Description

Technical Field

[0001] The present disclosure relates to an apparatus for detecting an object existing around a vehicle and controlling the vehicle. Background Art

[0002] Conventionally, there are known devices that detect information about objects (object information) present around a vehicle and control the vehicle based on the object information (see, for example, Patent Document 1). An example of such control is collision avoidance control.

[0003] Collision avoidance control is a control for avoiding a collision with an object around the vehicle. Examples of collision avoidance control include pre-crash safety control and front cross traffic alert control.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 2020-119183

[0007] Furthermore, in collision avoidance control, the computational processing for determining the possibility of collision between the vehicle and an object places a heavy load. Executing the computational processing for all objects included in the object information may make it difficult to complete the computational processing within a limited time.

[0008] Therefore, to reduce the computational processing load, one approach is to select a specified number (an upper limit) of objects from the multiple objects included in the object information. In other words, the number of objects subject to the computational processing is limited to the upper limit. In this case, objects with a low probability of collision with the vehicle are selected (extracted) from the object information. In other words, objects with a low probability of collision with the vehicle are excluded from the object information. Summary of the Invention

[0009] The present disclosure provides a technology capable of selecting an object that may collide with a vehicle from a plurality of objects included in object information.

[0010] A vehicle control device according to one or more embodiments includes:

[0011] A first sensor (14) acquires object information, the object information being information related to a plurality of objects existing in the surrounding area (Ara, Arb, and Arc) of the vehicle;

[0012] a second sensor (11) for detecting the speed (Vs) of the vehicle; and

[0013] A control unit (10), the control unit being configured to:

[0014] selecting, from the plurality of objects included in the object information, a plurality of objects existing in a predetermined area (As) as a first object group (OB1);

[0015] When a first number (Na) representing the number of objects included in the first object group is greater than a predetermined upper limit number (Nx), selecting objects up to the predetermined upper limit number from the first object group in descending order of priority (P) as a second object group (OB2); and

[0016] When the index value (Tc, ds) indicating the possibility of collision with the object included in the second object group satisfies a predetermined condition, collision avoidance control is executed.

[0017] The priority indicates the degree of possibility of collision with the vehicle.

[0018] Furthermore, the control unit is configured to lower the priority of specific objects included in the first object group when the speed (Vs) is less than or equal to a predetermined speed threshold (Vth). The specific objects are objects considered to move at a slower speed than a four-wheeled vehicle.

[0019] When the vehicle is traveling at a low speed, the probability of a specific object colliding with the vehicle is low. Taking this into account, the vehicle control device lowers the priority of specific objects when the vehicle's speed is below a speed threshold. By limiting the number of objects included in the second object group to an upper limit, the vehicle control device can reduce the probability of objects (specific objects) with a low probability of colliding with the vehicle being selected as the second object group. Therefore, the vehicle control device can select objects that may collide with the vehicle as the second object group. The vehicle control device can perform computational processing for collision avoidance control on objects that may collide with the vehicle while suppressing the computational processing load.

[0020] In one or more embodiments, the control unit is configured to calculate a reliability (Rd) for each object included in the first object group.

[0021] The reliability indicates the possibility that the object actually exists.

[0022] The control unit is configured to: when the first number (Na) is greater than the upper limit number (Nx), select a plurality of objects whose reliability (Rd) is greater than a specified reliability threshold (Rdth) from the first object group as a third object group (OB3).

[0023] The control unit is configured to: when the second number (Nb) which is the number of objects included in the third object group is greater than the upper limit number (Nx), select the upper limit number of objects from the third object group in descending order of priority as the second object group.

[0024] Furthermore, the control unit is configured to lower the priority of the specific object included in the third object group when the speed is equal to or less than the speed threshold.

[0025] According to the above configuration, the vehicle control device can select the second object group from among the third object group that is highly likely to actually exist.

[0026] In one or more embodiments, the control unit is configured to: when the first number (Na) is greater than the upper limit number (Nx), select multiple objects whose reliability (Rd) is less than the reliability threshold (Rdth) from the first object group as a fourth object group (OB4).

[0027] Furthermore, the control unit is configured to, if the second number (Nb) is less than the upper limit (Nx), select the third object group as the second object group, and then select a third number of objects from the fourth object group in descending order of priority as the second object group. The third number is the difference between the first number (Nx) and the second number (Nb).

[0028] Furthermore, the control unit is configured to lower the priority of the specific object included in the fourth object group when the speed is equal to or less than the speed threshold.

[0029] According to the above configuration, the vehicle control device can preferentially select the second object group from among the third object group that is highly likely to actually exist.

[0030] In one or more embodiments, the specific object is a pedestrian.

[0031] In one or more embodiments, the first sensor is configured to radiate electromagnetic waves and detect an object using information related to a reflection point of the electromagnetic waves. Furthermore, the first sensor is configured to determine that the object corresponding to the reflection point is the specific object when the reflection intensity at the reflection point is below a predetermined intensity threshold (Sth).

[0032] In one or more embodiments, the control unit is configured to determine the priority based on a distance (ds) between the vehicle and a predicted trajectory of the object or a distance (dw) between the vehicle and the object.

[0033] In one or more embodiments, the control unit may be implemented by a microprocessor programmed to perform one or more functions described in this specification. In one or more embodiments, the control unit may be implemented in whole or in part by hardware composed of one or more application-specific integrated circuits (ASICs).

[0034] In the above description, for components corresponding to one or more embodiments described later, the names and / or reference numerals used in the embodiments are enclosed in parentheses. However, the components are not limited to the embodiments specified by the names and / or reference numerals. Other objects, other features, and accompanying advantages of the present disclosure will be readily understood from the description of one or more embodiments described below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic configuration diagram of a vehicle control device according to one or more embodiments.

[0036] Figure 2 This diagram explains object information acquired by surrounding sensors.

[0037] Figure 3 This is a diagram showing the detectable range of each radar sensor.

[0038] Figure 4 This is a table for explaining the calculation method of the reliability Rd.

[0039] Figure 5 This diagram shows a situation where a vehicle is about to enter an intersection.

[0040] Figure 6 It is used for Figure 5 A diagram illustrating the processing contents in a two-dimensional coordinate system under the condition of .

[0041] Figure 7 This diagram shows a situation where a vehicle is about to enter an intersection.

[0042] Figure 8 This is a flowchart showing the “object detection routine” executed by the CPU of the collision avoidance ECU.

[0043] Figure 9 This is a flowchart showing the “first object selection routine” executed by the CPU of the collision avoidance ECU.

[0044] Figure 10This is a flowchart showing the “second object selection routine” executed by the CPU of the collision avoidance ECU.

[0045] Figure 11 This is a flowchart showing a “collision avoidance control execution routine” executed by the CPU of the collision avoidance ECU.

[0046] Description of Reference Numerals

[0047] 10: Collision avoidance ECU, 11: Vehicle speed sensor, 14: Surrounding sensor, 20: Engine ECU, 30: Brake ECU, 40: Instrument ECU. DETAILED DESCRIPTION

[0048] (Configuration of Vehicle Control Device)

[0049] like Figure 1 As shown, one or more vehicle control devices according to the embodiments are applied to a vehicle VA. The vehicle control device includes a collision avoidance ECU 10, an engine ECU 20, a brake ECU 30, and an instrument ECU 40. Some or all of these ECUs may be integrated into a single ECU. Hereinafter, the collision avoidance ECU 10 will be referred to as "ECU 10."

[0050] The ECU is an electric control unit (Electric Control Unit) including a microcomputer as a main component, and is connected to each other so as to be able to transmit and receive information via a CAN (Controller Area Network) (not shown).

[0051] A microcomputer includes a CPU (Central Processing Unit), ROM (Read-Only Memory), RAM (Random Access Memory), nonvolatile memory, and an interface (I / F). For example, ECU 10 includes a microcomputer including CPU 101, ROM 102, RAM 103, nonvolatile memory 104, and an interface (I / F) 105. CPU 101 is configured to implement various functions described below by executing instructions (programs, routines) stored in ROM 102.

[0052] The ECU 10 is configured to be connected to the following sensors to receive detection signals or output signals thereof.

[0053] The vehicle speed sensor 11 detects the speed (travel speed) of the vehicle VA and outputs a signal indicating the speed Vs. The steering angle sensor 12 detects the steering angle of the vehicle VA and outputs a signal indicating the steering angle θ (degrees). The yaw rate sensor 13 detects the yaw rate Yr of the vehicle VA and outputs a signal indicating the yaw rate Yr.

[0054] It should be noted that the steering angle θ and the yaw rate Yr are zero when the vehicle VA is traveling straight. The steering angle θ and the yaw rate Yr are positive when the vehicle VA is turning left, and negative when the vehicle VA is turning right.

[0055] Hereinafter, “information indicating the driving state of the vehicle VA” output from the sensors 11 to 13 may be referred to as “driving state information.” Note that the vehicle VA may further include sensors for acquiring other driving state information (eg, acceleration).

[0056] The surrounding sensor 14 obtains information related to three-dimensional objects present in the surrounding area of the vehicle VA. In this example, as described later, the surrounding area includes the front area, the right area, and the left area. Three-dimensional objects include, for example, moving objects such as four-wheeled vehicles, pedestrians, and bicycles, as well as stationary objects such as utility poles, trees, and guardrails. Hereinafter, these three-dimensional objects are referred to as "objects". The surrounding sensor 14 is configured to calculate and output information related to objects (hereinafter referred to as "object information").

[0057] like Figure 2 As shown, the surrounding sensor 14 acquires object information using a two-dimensional coordinate system defined by the x-axis and the y-axis. The origins of the x-axis and the y-axis are the center position O of the front portion of the vehicle VA in the vehicle width direction. The x-axis is a coordinate axis extending along the front-to-back direction of the vehicle VA through the center position O of the vehicle VA, with positive values indicating the front. The y-axis is a coordinate axis orthogonal to the x-axis, with positive values indicating the left direction of the vehicle VA.

[0058] The object information about the object (n) includes “the longitudinal distance Dfx(n), the lateral position Dfy(n), the relative speed Vfx(n), the orientation θp(n), the traveling direction, and the category, etc.” of the object (n).

[0059] Longitudinal distance Dfx(n) is the signed distance between object (n) and origin O in the x-axis direction. Transverse position Dfy(n) is the signed distance between object (n) and origin O in the y-axis direction. Relative velocity Vfx(n) is the velocity of object (n) in the x-axis direction relative to vehicle VA. In other words, relative velocity Vfx(n) is the difference between object (n)'s velocity Vn in the x-axis direction and vehicle VA's velocity Vs in the x-axis direction (= Vn - Vs). Direction θp(n) is the angle between the x-axis and the line connecting origin O and object (n). The direction of travel of object (n) is its relative direction of travel relative to vehicle VA.

[0060] The category of object (n) includes information indicating whether the object corresponds to a moving object or a stationary object. In this example, if the object is a moving object, the category of object (n) also includes information indicating whether the object (n) corresponds to a "vehicle" or an "object other than a vehicle." In this example, the "vehicle" in the category of object (n) refers to a "four-wheeled vehicle." Hereinafter, "objects other than vehicles" are referred to as "specific objects." Specific objects are objects that are considered to move at a slower speed than a four-wheeled vehicle, such as pedestrians.

[0061] Refer again Figure 1 The surrounding sensor 14 includes a plurality of radar sensors 15a, 15b, and 15c.

[0062] like Figure 3 As shown, radar sensor 15a is mounted on the right end of the front end portion of vehicle VA, radar sensor 15b is mounted in the center of the front end portion of vehicle VA, and radar sensor 15c is mounted on the left end of the front end portion of vehicle VA. It should be noted that when there is no need to distinguish between radar sensors 15a, 15b, and 15c, they are collectively referred to as "radar sensor 15."

[0063] Each radar sensor 15 radiates electromagnetic waves (e.g., radio waves in the millimeter wave band, referred to as "millimeter waves") and uses information related to the reflection point of the electromagnetic waves (reflection point information) to detect objects. Each radar sensor 15 includes a radar wave transceiver and an information processing unit. The radar wave transceiver radiates millimeter waves and receives millimeter waves reflected by objects within the radiation range (i.e., reflected waves). It should be noted that each radar sensor 15 may also use radio waves in a frequency band other than the millimeter wave band.

[0064] The information processing unit detects the object based on the reflection point information. The reflection point information includes the phase difference between the transmitted millimeter wave and the received reflected wave, the attenuation level of the reflected wave, and the time from transmitting the millimeter wave to receiving the reflected wave. Figure 2As shown, the information processing unit groups "multiple reflection points" (or multiple reflection points that are close to each other and move in the same direction) and detects the grouped reflection points (hereinafter referred to as "reflection point group") 201 as a single object (n). The information processing unit obtains (calculates) object information about object (n) based on the reflection point information. The information processing unit calculates object information about object (n) using any point (representative reflection point) 202 in reflection point group 201.

[0065] In this example, representative reflection point 202 is the reflection point with the highest reflection intensity in reflection point group 201. However, representative reflection point 202 is not limited thereto and may also be the left endpoint of reflection point group 201, the right endpoint of reflection point group 201, or a reflection point located between the left and right endpoints.

[0066] The information processing unit determines whether the object (n) corresponds to a moving object or a stationary object based on the change in the position of the object (n) relative to the vehicle VA. Furthermore, if the object (n) is a moving object, the information processing unit determines whether the object (n) is a vehicle (a four-wheeled vehicle) or a specific object (a pedestrian) based on the reflection intensity at the representative reflection point 202. Specifically, if the reflection intensity at the representative reflection point 202 is greater than a predetermined intensity threshold Sth, the information processing unit determines that the object (n) is a vehicle. On the other hand, if the reflection intensity at the representative reflection point 202 is less than the intensity threshold Sth, the information processing unit determines that the object (n) is a specific object.

[0067] like Figure 3 As shown, the radar sensor 15a's detectable area Ara is a sector-shaped area centered on a detection axis CL1 extending from the right end of the front end of the vehicle VA toward the right front, extending rightward to the right boundary line RBL1 and leftward to the left boundary line LBL1. The radius of this sector is a predetermined distance. The radar sensor 15a detects objects in the area Ara (the area to the right of the vehicle VA) and acquires (calculates) object information regarding the detected objects.

[0068] The radar sensor 15b's detectable area Arb is a sector-shaped area centered on a detection axis CL2 extending forward from the center of the front end of the vehicle VA in the vehicle width direction, extending rightward to the right boundary line RBL2 and leftward to the left boundary line LBL2. The radius of this sector is the aforementioned predetermined distance. The detection axis CL2 coincides with the front-rear axis FR of the vehicle VA. The radar sensor 15b detects objects in the area Arb (the area in front of the vehicle VA) and acquires (calculates) object information regarding the detected objects.

[0069] Similarly, the radar sensor 15c's detectable area Arc is a sector-shaped area centered on the detection axis CL3 extending from the left end of the front end of the vehicle VA toward the left front, extending rightward to the right boundary line RBL3 and leftward to the left boundary line LBL3. The radius of this sector is the predetermined distance described above. The radar sensor 15c detects objects within the area Arc (the area to the left of the vehicle VA) and acquires (calculates) object information regarding the detected objects.

[0070] The area Ara, Arb, and Arc together are sometimes referred to as a “detection area.” The ECU 10 acquires object information about an object (n) present in the detection area from the radar sensors 15a to 15c every time a predetermined time dt elapses.

[0071] Refer again Figure 1 The engine ECU 20 is connected to an engine actuator 21. The engine actuator 21 includes a throttle actuator that changes the throttle opening of a spark-ignition gasoline fuel injection internal combustion engine 22. The engine ECU 20 can change the torque generated by the internal combustion engine 22 by driving the engine actuator 21. The torque generated by the internal combustion engine 22 is transmitted to the drive wheels (not shown) via a transmission (not shown). Therefore, the engine ECU 20 can control the driving force by controlling the engine actuator 21, thereby changing the acceleration state (acceleration).

[0072] It should be noted that, when the vehicle VA is a hybrid vehicle, the engine ECU 20 can control the driving force generated by either or both of the internal combustion engine and the electric motor as the vehicle's driving source. Furthermore, when the vehicle VA is an electric vehicle, the engine ECU 20 can control the driving force generated by the electric motor as the vehicle's driving source.

[0073] The brake ECU 30 is connected to the brake actuator 31. The brake actuator 31 includes a hydraulic circuit. The hydraulic circuit includes a master cylinder, a flow path for the brake fluid, multiple valves, a pump, and a motor that drives the pump. The brake ECU 30 controls the brake actuator 31 to adjust the hydraulic pressure supplied to the wheel cylinders built into the brake mechanism 32. This hydraulic pressure generates friction braking force on the wheels. Therefore, the brake ECU 30 can control the braking force by controlling the brake actuator 31, thereby changing the acceleration state (deceleration, i.e., negative acceleration).

[0074] The instrument ECU 40 is connected to a display 41 and a speaker 42. The display 41 is a multi-information display located in front of the driver's seat. A head-up display can be used as the display 41. Based on instructions from the ECU 10, the instrument ECU 40 causes the display 41 to display a warning sign (e.g., a warning light). Furthermore, based on instructions from the ECU 10, the instrument ECU 40 causes the speaker 42 to output a warning sound.

[0075] (Extrapolation processing)

[0076] ECU 10 detects (identifies) object (n) based on the object information. ECU 10 performs extrapolation processing on the detected object (n). Extrapolation processing refers to the process of estimating the object information of an object (n) that is no longer detected when an object (n) detected at a certain point in time is temporarily undetected. Such extrapolation processing is well known (for example, Japanese Patent Application Publication No. 2015-137915 and Japanese Patent Application Publication No. 2019-2689). By performing extrapolation processing, ECU 10 can achieve uninterrupted detection of object (n).

[0077] (Reliability)

[0078] ECU 10 then calculates reliability Rd for object (n). Reliability Rd indicates the likelihood that object (n) actually exists. The greater the reliability Rd, the higher the probability that the object actually exists. Reliability Rd is, for example, a numerical value ranging from 0 to 100. Specifically, the minimum value of reliability Rd is "0," and the maximum value is "100." In this example, ECU 10 calculates reliability Rd as follows.

[0079] The ECU 10 acquires object information from the radar sensors 15a to 15c every time a time dt passes. The ECU 10 detects the object (n) based on the object information. Hereinafter, the time when the ECU 10 first detects the object (n) is referred to as the "detection start time."

[0080] like Figure 4 As shown, the ECU 10 sets the reliability Rd of object (n) to an initial value Rd_ini (e.g., 30) at the start of detection. At a time dt after the start of detection, the ECU 10 again acquires object information from the radar sensors 15a and 15c. If object (n) is detected at this time, the ECU 10 increases the reliability Rd of object (n) by a predetermined value Rd0 (>0). Specifically, as long as object (n) continues to be detected, the ECU 10 increments the reliability Rd of object (n) by Rd0 each time time dt passes.

[0081] Assume that object (n) is detected once and then no longer. In this case, ECU 10 performs the extrapolation process as described above to estimate object information for object (n). During the period when object (n) is not detected, ECU 10 performs the extrapolation process each time a time period dt elapses. In this case, ECU 10 measures the duration Ti of the extrapolation process. Duration Ti refers to the duration during which object (n) is not detected. It can be said that the longer duration Ti, the lower the probability that object (n) actually exists. Taking this into account, ECU 10 reduces reliability Rd as duration Ti increases.

[0082] Specifically, when the object (n) is no longer detected, the ECU 10 starts measuring the duration Ti of the extrapolation process for the object (n). When the object (n) is detected again, the ECU 10 ends measuring the duration Ti of the extrapolation process for the object (n).

[0083] like Figure 4 As shown, when the duration Ti is less than or equal to the first time Ta, the ECU 10 reduces the reliability Rd of the object (n) by the first value Rd1. The first time Ta is greater than or equal to the time dt.

[0084] When duration Ti is longer than first time Ta and less than second time Tb, ECU 10 reduces reliability Rd of object (n) by second value Rd2. Second time Tb is longer than first time Ta. Second value Rd2 is greater than first value Rd1. Therefore, the longer duration Ti is, the greater the reduction in reliability Rd.

[0085] It should be noted that when the duration Ti exceeds the second time Tb, the ECU 10 sets the reliability Rd of the object (n) to "0." In other words, the ECU 10 determines that the object (n) does not actually exist. Therefore, the ECU 10 deletes the object information related to the object (n). The calculation method for the reliability Rd is not limited to the method described above; other methods may also be used.

[0086] (Processing content in the two-dimensional coordinate system)

[0087] The ECU 10 executes the following processing in a two-dimensional coordinate system in order to execute collision avoidance control described later.

[0088] exist Figure 5 In the example shown in FIG1 , a vehicle VA is about to enter an intersection Is. In front of the vehicle VA, there is a first other vehicle OV1 and a first pedestrian PE1. The first other vehicle OV1 is traveling at the intersection Is. The first pedestrian PE1 is moving away from the vehicle VA.

[0089] In this example, if Figure 6 As shown, ECU 10 depicts a simplified representation of vehicle VA, a first other vehicle OV1, and a first pedestrian PE1 in a two-dimensional coordinate system. Specifically, ECU 10 depicts a first rectangle 410 representing the body of vehicle VA in the two-dimensional coordinate system. ROM 102 stores information related to the body size of vehicle VA. ECU 10 sets the size of first rectangle 410 based on this information. Furthermore, ECU 10 depicts a second rectangle 420 representing the body of first other vehicle OV1. It should be noted that the size of second rectangle 420 can be set based on the body size of an ordinary vehicle. Furthermore, ECU 10 depicts a third rectangle 430 representing first pedestrian PE1. Third rectangle 430 can be set based on the size of an ordinary person.

[0090] Based on the driving state information, the ECU 10 plots a first predicted trajectory tr1 on a two-dimensional coordinate system. The first predicted trajectory tr1 is the trajectory that the center position O of the vehicle VA will pass through between the current time point (the first time point) and a second time point, assuming that the vehicle VA maintains the driving state (speed Vs, yaw rate Yr, etc.) at the current time point. The second time point is a time point after a predetermined time t1 has passed from the current time point.

[0091] Based on the object information, the ECU 10 calculates the direction of travel and the speed Vo1 of the first other vehicle OV1. The ECU 10 then plots a second predicted trajectory tr2 on a two-dimensional coordinate system based on the direction and speed Vo1 of the first other vehicle OV1. The second predicted trajectory tr2 is the trajectory that a specific position 420a of the first other vehicle OV1 passes through between the current time point (the first time point) and the second time point, assuming that the first other vehicle OV1 maintains its current state (direction of travel and speed Vo1). In this example, the specific position 420a of the first other vehicle OV1 is the center position of the front portion of the first other vehicle OV1 in the vehicle width direction.

[0092] Based on the object information, the ECU 10 calculates the direction of travel of the first pedestrian PE1 and its speed Vo2. The ECU 10 then plots a third predicted trajectory tr3 on a two-dimensional coordinate system based on the direction and speed Vo2 of the first pedestrian PE1. The third predicted trajectory tr3 is the trajectory that the first pedestrian PE1 would pass through at the specific position 430a from the current time point (the first time point) to the second time point, assuming that the first pedestrian PE1 maintains the same state (the direction of travel and the speed Vo2) as at the current time point.

[0093] In this way, the ECU 10 can calculate the trajectory ( tr1 ) of the vehicle VA and the trajectories ( tr2 and tr3 ) of objects (the first other vehicle OV1 and the first pedestrian PE1 ) existing in the detection area in the two-dimensional coordinate system.

[0094] (Collision Avoidance Control)

[0095] The ECU 10 is configured to execute a well-known collision avoidance control when it is determined that a predetermined execution condition is satisfied based on a method described below. The collision avoidance control in this example is a control for avoiding a collision with an object approaching the vehicle VA from the right or left side of the vehicle VA.

[0096] Specifically, the ECU 10 selects a plurality of objects included in the object information. Figure 3 The multiple objects within the selected area As are shown. Hereinafter, the multiple objects selected in this manner will be referred to as the "first object group OB1." In this example, the objects selected as the first object group OB1 are "moving objects." The ECU 10 can select multiple moving objects as the first object group OB1 based on the object categories included in the object information.

[0097] The selection area As is set to select (extract) objects moving from the right side area of the vehicle VA to the vehicle VA and objects moving from the left side area of the vehicle VA to the vehicle VA. Specifically, the selection area As includes a first area As1 and a second area As2. The first area As1 is an area extending from the vehicle front-rear axis FR of the vehicle VA in the right direction by a length Lh, and is an area for selecting objects moving from the right side area of the vehicle VA to the vehicle VA. The width WA1 of the first area As1 in the front-rear direction of the vehicle VA gradually increases as it approaches the right direction. The second area As2 is an area extending from the vehicle front-rear axis FR of the vehicle VA in the left direction by a length Lh, and is an area for selecting objects moving from the left side area of the vehicle VA to the vehicle VA. The width WA2 of the second area As2 in the front-rear direction of the vehicle VA gradually increases as it approaches the left direction.

[0098] Next, the ECU 10 selects objects whose number is less than or equal to a predetermined upper limit Nx from the first object group OB1. The plurality of objects thus selected are hereinafter referred to as the "second object group OB2." The method of selecting the second object group OB2 will be described in detail below.

[0099] The computational processing for determining the likelihood of collision between the vehicle VA and an object, described below, carries a heavy load. When executing computational processing on all objects included in the first object group OB1, it can be difficult to complete the computational processing within a limited timeframe. The upper limit Nx is set to reduce the processing load on the ECU 10. This upper limit Nx is set to a value of 2 or greater, taking into account the processing capacity of the ECU 10. Thus, considering the processing load on the ECU 10, the number of objects included in the second object group OB2 is limited to the upper limit Nx. This allows the ECU 10 to complete the computational processing within a limited timeframe.

[0100] The ECU 10 determines whether or not there is an object (hereinafter referred to as a “target object”) that may collide with the vehicle VA in the second object group OB2 .

[0101] exist Figure 5 In the example, it is assumed that the ECU 10 selects the first other vehicle OV1 and the first pedestrian PE1 as the second object group OB2. The ECU 10 uses the information on the two-dimensional coordinate system to determine whether the target object exists in the second object group OB2. The ECU 10 determines whether there is a trajectory that intersects with the first predicted trajectory tr1. Figure 6 In the example, the first predicted trajectory tr1 intersects the second predicted trajectory tr2. Therefore, the first other vehicle OV1 corresponding to the second predicted trajectory tr2 is an object that may collide with the vehicle VA. The ECU 10 selects the first other vehicle OV1 as the target object. On the other hand, since the first predicted trajectory tr1 does not intersect the third predicted trajectory tr3, the ECU 10 does not select the first pedestrian PE1 as the target object.

[0102] Next, the ECU 10 determines whether a predetermined execution condition is satisfied for the target object. The execution condition is a condition for determining whether to execute (start) the collision avoidance control.

[0103] The execution condition is a condition related to an index value indicating the likelihood of collision with the control target. In this example, the index value is the time Tc required for the vehicle VA to reach the route (second predicted trajectory tr2) of the control target (first other vehicle OV1). It should be noted that time Tc can also be considered the margin of time before the vehicle VA and the first other vehicle OV1 collide.

[0104] Specifically, if Figure 6As shown, the ECU 10 determines the intersection position ps1 where the first predicted trajectory tr1 intersects the second predicted trajectory tr2. The ECU 10 then determines the time Tc required for the center position O of the vehicle VA to reach the intersection position ps1 based on driving state information (e.g., speed Vs and yaw rate Yr). For example, the ECU 10 can determine the time Tc by dividing the distance ds between the vehicle VA and the intersection position ps1 by the speed Vs.

[0105] When the time Tc is equal to or shorter than a predetermined time threshold value Tcth, the ECU 10 determines that the execution condition is satisfied and executes the collision avoidance control.

[0106] Note that, when there are a plurality of control objects, the ECU 10 determines whether the execution condition is satisfied for each control object.

[0107] Collision avoidance control includes driving force suppression control, which suppresses the driving force of the vehicle VA; braking force control, which applies braking force to the wheels; and caution control, which calls the driver's attention. Specifically, the ECU 10 transmits a driving instruction signal to the engine ECU 20. Upon receiving the driving instruction signal from the ECU 10, the engine ECU 20 controls the engine actuator 21 to suppress the driving force so that the actual acceleration of the vehicle VA matches the target acceleration AG (e.g., zero) included in the driving instruction signal. Furthermore, the ECU 10 transmits a braking instruction signal to the brake ECU 30. Upon receiving the braking instruction signal from the ECU 10, the brake ECU 30 controls the brake actuator 31 to apply braking force to the wheels so that the actual acceleration of the vehicle VA matches the target deceleration TG included in the braking instruction signal. Furthermore, the ECU 10 transmits a caution instruction signal to the meter ECU 40. Upon receiving the caution instruction signal from the ECU 10, the meter ECU 40 displays a caution instruction mark on the display 41 and outputs an alarm sound from the speaker 42.

[0108] (Selection of the second object group)

[0109] Next, a method for selecting the second object group OB2 will be described. The ECU 10 selects the second object group OB2 from the plurality of objects included in the first object group OB1 according to the following method.

[0110] The method of selecting the second object group OB2 will be described below for situations A and B. Hereinafter, the number of objects included in the first object group OB1 will be referred to as "first number Na."

[0111] (Situation A): The first number Na is less than the upper limit number Nx (ie, Na≤Nx).

[0112] (Situation B): The first number Na is greater than the upper limit number Nx (ie, Na>Nx).

[0113] In the situation A, the ECU 10 selects all objects included in the first object group OB1 as the second object group OB2 .

[0114] In situation B, the ECU 10 first selects objects from the first object group OB1 whose reliability Rd is greater than or equal to a predetermined reliability threshold Rth. The objects thus selected are referred to as the "third object group OB3." Furthermore, the number of objects included in the third object group OB3 is referred to as the "second number Nb." The third object group OB3 includes multiple objects with a high probability of actually existing.

[0115] Next, the ECU 10 selects objects from the first object group OB1 whose reliability Rd is less than the reliability threshold Rth. These selected objects are referred to as the "fourth object group OB4." In other words, the ECU 10 selects objects from the first object group OB1 that were not included in the third object group OB3 as the fourth object group OB4. The fourth object group OB4 includes multiple objects whose probability of actually existing is lower than that of the third object group OB3.

[0116] Here, any of the following situations B-1 to B-3 may occur.

[0117] (Situation B-1): The second number Nb is the same as the upper limit number Nx (ie, Nb=Nx).

[0118] (Situation B-2): The second number Nb is greater than the upper limit number Nx (ie, Nb>Nx).

[0119] (Situation B-3): The second number Nb is smaller than the upper limit number Nx (ie, Nb<Nx).

[0120] Hereinafter, the method of selecting the second object group OB2 will be described for each of situations B-1 to B-3.

[0121] (Situation B-1)

[0122] The ECU 10 selects all objects included in the third object group OB3 as the second object group OB2 .

[0123] (Situation B-2)

[0124] The ECU 10 calculates a priority P for each object included in the third object group OB3. Priority P indicates the likelihood of a collision with the vehicle VA. The greater the priority P, the higher the likelihood of a collision between the object and the vehicle VA. In this example, priority P is calculated based on the distance between the vehicle VA and the predicted trajectory of the object in the two-dimensional coordinate system.

[0125] exist Figure 6 In the example, ECU 10 calculates the priority P of the first other vehicle OV1 as follows. ECU 10 calculates the distance ds between the center position O of vehicle VA and the intersection position ps1. ECU 10 calculates the priority P by applying the distance ds to a predetermined first priority map Map1 (ds). The first priority map Map1 defines the relationship between the distance ds and the priority P. The smaller the distance ds, the greater the priority P. In other words, the closer the vehicle VA is to the predicted trajectory of the object (in Figure 6 In the example, the second predicted trajectory tr2), the greater the priority P.

[0126] It should be noted that in Figure 6 In the example, the third predicted trajectory tr3 of the first pedestrian PE1 does not intersect the first predicted trajectory tr1 of the vehicle VA. In this case, the ECU 10 sets the priority P of the first pedestrian PE1 to a predetermined minimum value. This reduces the likelihood that the first pedestrian PE1 (i.e., an object with a low probability of collision with the vehicle VA) will be selected as part of the second object group OB2.

[0127] Next, the ECU 10 determines whether the speed Vs of the vehicle VA is below a predetermined speed threshold Vth. The speed threshold Vth is a threshold used to determine whether the vehicle VA is traveling at a low speed. If the speed Vs is below the speed threshold Vth, the ECU 10 reduces the priority P of the specific objects included in the third object group OB3 by a predetermined value Pd (>0). As described above, the specific objects are objects (pedestrians) that move at a lower speed than four-wheeled vehicles. If the vehicle VA is traveling at a low speed, it can be said that the possibility of the vehicle VA colliding with the specific objects is low. Taking this into account, the ECU 10 reduces the priority P of the specific objects. This reduces the possibility of the specific objects being selected as part of the second object group OB2.

[0128] It should be noted that, when the speed Vs of the vehicle VA is greater than the speed threshold Vth, the ECU 10 does not change the priority P of the specific object.

[0129] The ECU 10 selects Nx (upper limit) objects from the third object group OB3 in descending order of priority P as the second object group OB2 .

[0130] Work Example 1

[0131] use Figure 7 Operation Example 1 of the ECU 10 in the situation B-2 will be described. In this example, the upper limit number Nx is "2" for simplicity of description.

[0132] The vehicle VA is traveling at a low speed toward the intersection Is1. That is, the speed Vs is less than or equal to the speed threshold Vth. In front of the vehicle VA, there are a first other vehicle OV1, a second other vehicle OV2, a first pedestrian PE1, and a second pedestrian PE2.

[0133] The ECU 10 detects the first other vehicle OV1, the second other vehicle OV2, the first pedestrian PE1, and the second pedestrian PE2 based on the object information, and detects the first pedestrian PE1 and the second pedestrian PE2 as specific objects.

[0134] The selected area As includes the four objects (OV1, OV2, PE1, and PE2). Therefore, the ECU 10 selects the four objects (OV1, OV2, PE1, and PE2) as the first object group OB1. The reliability Rd of each of the four objects (OV1, OV2, PE1, and PE2) is greater than the reliability threshold Rth. The ECU 10 selects the four objects (OV1, OV2, PE1, and PE2) as the third object group OB3.

[0135] The second number Nb (=4) is greater than the upper limit number Nx (=2). ECU 10 calculates the priority P for each object (OV1, OV2, PE1, and PE2). Hereinafter, the priority P of the first other vehicle OV1 will be referred to as "Pov1," the priority P of the second other vehicle OV2 will be referred to as "Pov2," the priority P of the first pedestrian PE1 will be referred to as "Ppe1," and the priority P of the second pedestrian PE2 will be referred to as "Ppe2."

[0136] The predicted trajectories of the first pedestrian PE1, the second pedestrian PE2, the first other vehicle OV1, and the second other vehicle OV2 are "tr11," "tr12," "tr13," and "tr14," respectively. The intersection position of the predicted trajectory tr11 of the first pedestrian PE1 and the first predicted trajectory tr1 is "ps11," the intersection position of the predicted trajectory tr12 of the second pedestrian PE2 and the first predicted trajectory tr1 is "ps12," the intersection position of the predicted trajectory tr13 of the first other vehicle OV1 and the first predicted trajectory tr1 is "ps13," and the intersection position of the predicted trajectory tr14 of the second other vehicle OV2 and the first predicted trajectory tr1 is "ps14." The intersection position ps11 corresponding to the first pedestrian PE1 is closest to the vehicle VA among the four intersection positions. The intersection position ps12 corresponding to the second pedestrian PE2 is the second closest to the vehicle VA among the four intersection positions. The intersection position ps13 corresponding to the first other vehicle OV1 is the third closest to the vehicle VA among the four intersection positions. The intersection position ps14 corresponding to the second other vehicle OV2 is farthest from the vehicle VA among the four intersection positions. Therefore, when the ECU 10 calculates the priority P for each of the four objects using the first priority map Map1, the magnitude relationship between the four priorities Pov1, Pov2, Ppe1, and Ppe2 is as follows.

[0137] Ppe1>Ppe2>Pov1>Pov2

[0138] Because speed Vs is below speed threshold Vth, ECU 10 reduces the priority P of the specific object by value Pd. Specifically, ECU 10 reduces priority Ppe1 for the first pedestrian PE1 by value Pd. Furthermore, ECU 10 reduces priority Ppe2 for the second pedestrian PE2 by value Pd. As a result, the magnitude relationship between the four priorities Pov1, Pov2, Ppe1, and Ppe2 is as follows.

[0139] Pov1>Pov2>Ppe1>Ppe2

[0140] The ECU 10 selects Nx (=2) objects from the third object group OB3 as the second object group OB2 in descending order of priority P. Therefore, the first other vehicle OV1 and the second other vehicle OV2 are ultimately selected as the second object group OB2.

[0141] When the vehicle VA is traveling at a low speed, specific objects (PE1 and PE2) moving at a slower speed than a four-wheeled vehicle are less likely to collide with the vehicle VA. The ECU 10 can lower the priorities (Ppe1 and Ppe2) of the specific objects (PE1 and PE2) to reduce the likelihood that these specific objects will be selected as part of the second object group OB2. Even when the number of objects included in the second object group OB2 is limited to an upper limit Nx to account for the processing load on the ECU 10, the ECU 10 can still select objects with a high probability of collision with the vehicle VA as part of the second object group OB2.

[0142] (Situation B-3)

[0143] The ECU 10 first selects all objects (Nb objects) included in the third object group OB3 as the second object group OB2. Therefore, the ECU 10 preferentially selects the third object group OB3, which is highly likely to actually exist, as the second object group OB2.

[0144] Next, the ECU 10 calculates the priority P for each object included in the fourth object group OB4 as described above. The ECU 10 determines whether the speed Vs of the vehicle VA is below the speed threshold Vth. If the speed Vs is below the speed threshold Vth, the ECU 10 reduces the priority P of the specific objects included in the fourth object group OB4 by a value Pd.

[0145] Note that, when the speed Vs of the vehicle VA is greater than the speed threshold Vth, the ECU 10 does not change the priority P of the specific objects included in the fourth object group OB4 .

[0146] The ECU 10 selects a third number, Nc, of objects from the fourth object group OB4, in descending order of priority P, as the second object group OB2. The third number, Nc, is the difference between the upper limit number, Nx, and the second number, Nb (Nc = Nx - Nb). Therefore, the ECU 10 ultimately selects Nx (the upper limit number), objects as the second object group OB2.

[0147] Work Example 2

[0148] use Figure 7 Operation Example 2 of the ECU 10 in the situation B-3 will be described. In this example, the upper limit number Nx is also "2".

[0149] Operation Example 2 differs from Operation Example 1 in the following respects. The reliability Rd of the first other vehicle OV1 is greater than the reliability threshold Rth. Therefore, the ECU 10 selects the first other vehicle OV1 as the third object group OB3. On the other hand, the reliability Rd of the objects other than the first other vehicle OV1 (OV2, PE1, and PE2) is less than the reliability threshold Rth. Therefore, the ECU 10 selects the three objects (OV2, PE1, and PE2) as the fourth object group OB4.

[0150] The second number Nb (=1) is smaller than the upper limit number Nx (=2). The ECU 10 first selects the first other vehicle OV1 included in the third object group OB3 as the second object group OB2.

[0151] The ECU 10 calculates the priority P for each of the three objects (OV2, PE1, and PE2) included in the fourth object group OB4. When the ECU 10 calculates the priority P for each of the three objects using the first priority map Map1, the magnitude relationship between the three priorities Pov2, Ppe1, and Ppe2 is as follows.

[0152] Ppe1>Ppe2>Pov2

[0153] Because speed Vs is below speed threshold Vth, the ECU 10 reduces the priority P of the specific objects included in the fourth object group OB4 by the value Pd. Specifically, the ECU 10 reduces the priority Ppe1 of the first pedestrian PE1 by the value Pd. Furthermore, the ECU 10 reduces the priority Ppe2 of the second pedestrian PE2 by the value Pd. As a result, the relationship between the three priorities Pov2, Ppe1, and Ppe2 is as follows.

[0154] Pov2>Ppe1>Ppe2

[0155] The ECU 10 selects the third number Nc (=1) of objects from the fourth object group OB4, in descending order of priority P, as the second object group OB2. Specifically, the ECU 10 selects the second other vehicle OV2 as the second object group OB2. Consequently, the first other vehicle OV1 and the second other vehicle OV2 are ultimately selected as the second object group OB2.

[0156] According to this configuration, even when the number of objects included in the second object group OB2 is limited to the upper limit number Nx in consideration of the processing load in the ECU 10 , the ECU 10 can select objects with a high probability of colliding with the vehicle VA as the second object group OB2 .

[0157] (Work)

[0158] The CPU 101 of the ECU 10 (hereinafter referred to as "CPU") is configured to execute each of the following operations every time a time dt elapses: Figures 8 to 11 routine.

[0159] It should be noted that the CPU acquires running state information from the various sensors 11 to 13 and object information from the surrounding sensor 14 every time the time dt elapses, and stores these pieces of information in the RAM 103 .

[0160] When the specified timing is reached, the CPU Figure 8 The process starts at step 800 and the processes of steps 801 to 804 described below are sequentially executed. Then, the CPU proceeds to step 895 to end this routine.

[0161] Step 801 : The CPU detects an object existing in the surrounding area based on the object information acquired from the surrounding sensor 14 .

[0162] Step 802: The CPU performs the extrapolation process as described above. Thus, the CPU estimates the object information of the object that is no longer detected.

[0163] Step 803: The CPU selects objects in the selection area As as the first object group OB1.

[0164] Step 804: The CPU calculates the reliability Rd for each object included in the first object group OB1.

[0165] When the specified timing is reached, the CPU Figure 9 Processing begins at step 900 and proceeds to step 901, where it determines whether the first number Na is less than or equal to the upper limit number Nx. If the first number Na is less than or equal to the upper limit number Nx, this corresponds to situation A described above. The CPU determines "yes" in step 901 and proceeds to step 902. The CPU selects all objects included in the first object group OB1 as the second object group OB2. The CPU then proceeds to step 995, terminating this routine.

[0166] On the other hand, when the first number Na is greater than the upper limit number Nx, this corresponds to the above-mentioned situation B. The CPU determines "No" in step 901 and proceeds to step 903 to execute the following steps. Figure 10 In Figure 10 In the routine of , the processing of selecting the second object group OB2 is executed. Then, the CPU proceeds to step 995 and ends this routine.

[0167] When the CPU enters Figure 9 At step 903 of the routine, the CPU Figure 10The process begins at step 1000 and proceeds to step 1001. In step 1001, the CPU selects objects from the first object group OB1 whose reliability Rd is greater than or equal to a reliability threshold Rth as a third object group OB3. Furthermore, the CPU selects objects from the first object group OB1 whose reliability Rd is less than the reliability threshold Rth as a fourth object group OB4.

[0168] Next, the CPU compares the second number Nb with the upper limit number Nx in step 1002. That is, the CPU determines which of the above-mentioned situations B-1 to B-3 the current situation is.

[0169] If the second number Nb is the same as the upper limit number Nx (i.e., Nb=Nx), this corresponds to situation B-1. In this case, the CPU proceeds to step 1003 and selects all objects included in the third object group OB3 as the second object group OB2. Then, the CPU proceeds to step 1095 and ends this routine. Then, the CPU proceeds from step 1096. Figure 9 Step 903 of the routine proceeds to step 995.

[0170] If the second number Nb is greater than the upper limit number Nx (ie, Nb>Nx), this corresponds to situation B-2. In this case, the CPU proceeds from step 1002 to step 1004 to calculate the priority P for each object included in the third object group OB3.

[0171] Next, the CPU determines in step 1005 whether the speed Vs of the vehicle VA is below the speed threshold Vth. If the speed Vs of the vehicle VA is below the speed threshold Vth, the CPU determines "yes" in step 1005 and proceeds to step 1006. The CPU reduces the priority P of the specific objects included in the third object group OB3 by a value Pd. Next, the CPU proceeds to step 1007 and selects an upper limit number Nx of objects from the third object group OB3 in descending order of priority P as the second object group OB2. Then, the CPU proceeds to step 1095 and ends this routine. Then, the CPU proceeds to step 1096. Figure 9 Step 903 of the routine proceeds to step 995.

[0172] It should be noted that if the speed Vs of the vehicle VA is not less than the speed threshold Vth, the CPU determines "No" in step 1005 and proceeds directly to step 1007. The CPU then selects an upper limit of Nx objects from the third object group OB3 in descending order of priority P to form the second object group OB2.

[0173] If the second number Nb is less than the upper limit Nx (i.e., Nb < Nx), this corresponds to situation B-3. In this case, the CPU proceeds from step 1002 to step 1008, where it selects all objects included in the third object group OB3 as the second object group OB2. Next, in step 1009, the CPU calculates the priority P for each object included in the fourth object group OB4.

[0174] Next, the CPU determines in step 1010 whether the speed Vs of the vehicle VA is below the speed threshold Vth. If the speed Vs of the vehicle VA is below the speed threshold Vth, the CPU determines "yes" in step 1010 and proceeds to step 1011. The CPU reduces the priority P of the specific objects included in the fourth object group OB4 by the value Pd. Next, the CPU proceeds to step 1012 and selects the third number Nc (=Nx-Nb) of objects from the fourth object group OB4 in descending order of priority P as the second object group OB2. Then, the CPU proceeds to step 1095 and ends this routine. Then, the CPU proceeds to step 1096 and ends this routine. Figure 9 Step 903 of the routine proceeds to step 995.

[0175] It should be noted that if the speed Vs of the vehicle VA is not less than the speed threshold Vth, the CPU determines "No" in step 1010 and proceeds directly to step 1012. The CPU then selects the third number Nc of objects from the fourth object group OB4 in descending order of priority P to form the second object group OB2.

[0176] Then, when the predetermined timing is reached, the CPU Figure 11 Processing begins at step 1100 and proceeds to step 1101, where it determines whether the target object exists within the second object group OB2. Specifically, the CPU uses the information in the two-dimensional coordinate system as described above to determine whether the target object exists within the second object group OB2. If the target object does not exist, the CPU returns a "No" determination in step 1101 and proceeds directly to step 1195, terminating this routine.

[0177] In contrast, if the target object is present, the CPU returns a "yes" determination in step 1101 and proceeds to step 1102, where it determines whether the aforementioned execution condition is met for the target object. Specifically, the CPU determines whether time Tc is less than or equal to time threshold Tcth. If the execution condition is not met, the CPU returns a "no" determination in step 1102 and proceeds directly to step 1195, terminating the routine.

[0178] On the other hand, if the execution condition is satisfied, the CPU makes a "yes" determination in step 1102 and proceeds to step 1103 to execute the collision avoidance control. The CPU then proceeds to step 1195 to terminate this routine.

[0179] The vehicle control device with the above configuration achieves the following effects. When the vehicle VA is traveling at a low speed, a specific object (pedestrian) moving at a slower speed than a four-wheeled vehicle is less likely to collide with the vehicle VA. Taking this into account, when the speed Vs of the vehicle VA is below the speed threshold Vth, the vehicle control device reduces the priority P of the specific object by a value Pd. By limiting the number of objects included in the second object group OB2 to an upper limit number Nx, the vehicle control device can reduce the likelihood of specific objects being selected as part of the second object group OB2. Consequently, the vehicle control device can select objects that are likely to collide with the vehicle VA as part of the second object group OB2. The vehicle control device can perform computational processing for collision avoidance control on objects that are likely to collide with the vehicle VA while suppressing the computational processing load.

[0180] It should be noted that the present disclosure is not limited to the above-described embodiment, and various modifications can be adopted within the scope of the present disclosure.

[0181] (Variation 1)

[0182] In the above embodiment, the ECU 10 selects the second object group OB2 from the third object group OB3 and / or the fourth object group OB4, but this configuration is not limiting. The ECU 10 may also select the second object group OB2 directly from the first object group OB1 as described below. After selecting the first object group OB1, the ECU 10 calculates the priority P for each object included in the first object group OB1. If the first number Na is greater than the upper limit number Nx, the ECU 10 selects the upper limit number Nx of objects from the first object group OB1 in descending order of priority P as the second object group OB2. In this configuration, the ECU 10 lowers the priority P of specific objects included in the first object group OB1 when the speed Vs of the vehicle VA is below the speed threshold Vth. This configuration reduces the likelihood that specific objects included in the first object group OB1 will be selected as the second object group OB2.

[0183] (Variation 2)

[0184] The specific object is an object that is considered to move slower than a four-wheeled vehicle, and may be, for example, a bicycle.

[0185] (Variation 3)

[0186] The calculation method of the priority P is not limited to the above example. The ECU 10 may also calculate the priority P based on the distance dw between the vehicle VA and the object in the two-dimensional coordinate system. Figure 6 In the example, ECU 10 can also determine priority P for the first other vehicle OV1 as follows. ECU 10 calculates distance dw between the center position O of vehicle VA and specific position 420a of the first other vehicle OV1. ECU 10 determines priority P by applying distance dw to a predetermined second priority map Map2(dw). Second priority map Map2 defines the relationship between distance dw and priority P. The smaller the distance dw, the greater the priority P.

[0187] exist Figure 6 In the example, the ECU 10 can also calculate the priority P of the first other vehicle OV1 as follows. The ECU 10 calculates the time Tc required for the center position O of the vehicle VA to reach the intersection position ps1. The ECU 10 calculates the priority P by applying the time Tc to a predetermined third priority map Map3(Tc). The third priority map Map3 defines the relationship between time Tc and priority P. The shorter the time Tc, the greater the priority P.

[0188] The ECU 10 may determine the priority P of the first other vehicle OV1 based on the running state (eg, speed) of the first other vehicle OV1 . Furthermore, the ECU 10 may determine the priority P of the first other vehicle OV1 based on the relative speed Vfx of the first other vehicle OV1 to the vehicle VA.

[0189] (Variation 4)

[0190] Alternatively, when lowering the priority P of the specific object, the ECU 10 may change the value Pd according to the specific object's speed in the direction of travel. For example, the ECU 10 may change the value Pd so that the lower the specific object's speed, the larger the value Pd. This is because the lower the specific object's speed, the lower the probability of the specific object colliding with the vehicle VA.

[0191] (Variant 5)

[0192] The selection area As is not limited to the above-mentioned shape and may be set to other shapes as long as it can select (extract) objects moving from the right side area of the vehicle VA toward the vehicle VA and objects moving from the left side area of the vehicle VA toward the vehicle VA.

[0193] (Variant 6)

[0194] Alternatively, the ECU 10 may select the second object group OB2 before (for example, executing Figure 10), exclude objects with a low possibility of collision with the vehicle VA from the first object group OB1 (for example, Figure 5 The first person PE1).

[0195] (Variant 7)

[0196] The surrounding sensors 14 may include sensors other than radar sensors. They may also include LiDAR (Light Detection and Ranging / Laser Imaging Detection and Ranging) and / or camera sensors. The camera sensor acquires image data of the area surrounding the vehicle VA. The camera sensor may also pre-store data representing patterns of objects such as four-wheeled vehicles and pedestrians. The camera sensor can identify which of the four-wheeled vehicles and pedestrians (specific objects) the object corresponds to by performing pattern matching on the image data.

[0197] (Variation 8)

[0198] The execution condition is not limited to the above example. The index value indicating the possibility of collision with the object may be the distance ds. The execution condition may also be a condition that is satisfied when the distance ds is less than a predetermined distance threshold dsth.

Claims

1. A vehicle control device comprising: a first sensor for acquiring object information, wherein the object information is information related to a plurality of objects existing in a surrounding area of the vehicle; a second sensor, detecting the speed of the vehicle; as well as A control unit, the control unit being configured to: selecting, from the plurality of objects included in the object information, a plurality of objects existing in a predetermined area as a first object group; When a first number, which is the number of objects included in the first object group, is greater than a predetermined upper limit, selecting objects up to the predetermined upper limit from the first object group in descending order of priority as a second object group; as well as executing collision avoidance control when an index value indicating the possibility of collision with an object included in the second object group satisfies a predetermined condition; The priority indicates the possibility of collision with the vehicle. Furthermore, the control unit is configured to, when the speed is equal to or less than a predetermined speed threshold, lower the priority of a specific object included in the first object group; The specific object is considered to be an object moving at a speed slower than that of a four-wheeled vehicle. The control unit is configured to calculate reliability for each object included in the first object group, The reliability indicates the possibility that the object actually exists. The control unit is configured to: if the first number is greater than the upper limit, select, from the first object group, a plurality of objects whose reliability is greater than or equal to a predetermined reliability threshold as a third object group; The control unit is configured to, when the second number, which is the number of objects included in the third object group, is greater than the upper limit, select objects up to the upper limit from the third object group in descending order of priority as the second object group; The control unit is configured to lower the priority of the specific object included in the third object group when the speed is equal to or less than the speed threshold.

2. The vehicle control device according to claim 1, wherein: The control unit is configured to: if the first number is greater than the upper limit, select a plurality of objects whose reliability is less than the reliability threshold from the first object group as a fourth object group; Furthermore, the control unit is configured to: if the second number is less than the upper limit, select the third object group as the second object group, and then select a third number of objects from the fourth object group in descending order of priority as the second object group; The third number is the difference between the first number and the second number, The control unit is configured to, when the speed is equal to or less than the speed threshold, lower the priority of the specific object included in the fourth object group.

3. The vehicle control device according to claim 1, wherein: The specific object is a pedestrian.

4. The vehicle control device according to claim 1, wherein: The first sensor is configured to: radiate electromagnetic waves, and detect an object using information related to a reflection point of the electromagnetic waves, The first sensor is configured to determine that the object corresponding to the reflection point is the specific object when the reflection intensity at the reflection point is equal to or less than a predetermined intensity threshold.

5. The vehicle control device according to claim 1, wherein: The control unit is configured to determine the priority based on a distance between the vehicle and a predicted trajectory of the object, or a distance between the vehicle and the object.

Images