Vehicle travel control device

Abstract

To provide a travel control device capable of executing travel control by accurately detecting a distance to a low structure without requiring an expensive sensor such as a LiDAR.SOLUTION: A vehicle travel control device includes a camera sensor and a radar sensor capable of measuring a distance to a target as a first distance and a second distance, respectively, and a driving support ECU that executes travel control, wherein the driving support ECU stores a relationship between a plurality of first distances obtained in advance and a correction coefficient for obtaining a fusion distance based on the first distance and the second distance based on the first distance. When it is determined that the specific structure is present in the predetermined area (S60), a correction coefficient Ki is obtained from the relation on the basis of the first distances about the specific structure (S90), and travel control is executed about the specific structure on the basis of fusion distances obtained as products of the correction coefficient and the first distances (S100, S110).SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a cruise control device for a vehicle such as an automobile. [Background technology]

[0002] One type of cruise control device is known that, when it is determined that an obstacle such as a pedestrian is present ahead of the host vehicle, performs cruise control to reduce the risk of collision between the host vehicle and the obstacle. For example, Patent Document 1 listed below describes a cruise control device that automatically applies the brakes to decelerate the vehicle as cruise control to reduce the risk of collision between the host vehicle and the pedestrian. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-182768 Summary of the Invention

[0004] [Problem to be solved by the invention] Depending on the driving conditions of the host vehicle, such as when the host vehicle is traveling at an angle to the road, there may be a low structure, such as a curb or a step, between the host vehicle and the pedestrian. If the host vehicle passes over a structure, such as a curb or a step, the behavior of the host vehicle becomes unstable, and there is a risk that driving control that reduces the risk of a collision between the host vehicle and the pedestrian will not be performed appropriately.

[0005] In driving control to reduce the risk of collision, generally, a fusion process is performed based on the detection results of a camera sensor and a radar sensor, thereby detecting an obstacle ahead of the vehicle and the distance to the obstacle with high accuracy. However, when the detection target is a low-height structure, it is difficult for the radar sensor to detect the target and the fusion process becomes complicated, making it impossible to accurately detect the distance to the detection target.

[0006] It is also possible to use LiDAR to accurately detect the distance to low-height structures, but LiDAR is more expensive than radar sensors, which inevitably makes the driving control device expensive.

[0007] The present invention provides a driving control device that performs driving control to reduce the risk of collision between the vehicle and an obstacle, and that can accurately detect the distance to a low-height structure and perform driving control without requiring an expensive sensor such as LiDAR. [Means for solving the problems and effects of the invention]

[0008] According to the present invention, there is provided a vehicle driving control device (100) including a camera sensor (12) and a radar sensor (14) capable of measuring the distance to a target as a first distance (Lc) and a second distance (Ll), respectively, and a control unit (driving assistance ECU 10) that, when it is determined based on the detection results of the camera sensor and the radar sensor that an obstacle is present in a predetermined area in the traveling direction of the vehicle, performs driving control to reduce the risk of collision between the vehicle (102) and the obstacle.

[0009] The control unit (driving assistance ECU10) stores a relationship between a first distance and a correction coefficient (Ki) that is determined in advance for a plurality of first distances (Lci), where the correction coefficient is a coefficient for the first distance for determining a fusion distance (Lfi) based on the first distance and the second distance, and when the control unit (driving assistance ECU10) determines that a specific structure (126) that can be measured by the camera sensor (12) but whose accurate measurement by the radar sensor (14) is difficult is present in a predetermined area (S60), the control unit (driving assistance ECU10) determines the correction coefficient (Ki) from the relationship based on the first distance (Lci) to the specific structure (S90), determines the fusion distance (Lfi) to the specific structure as the product of the determined correction coefficient and the first distance to the specific structure (S100), and performs driving control for the specific structure based on the determined fusion distance to the specific structure (S110).

[0010] According to the above configuration, a correction coefficient is calculated from the relationship based on the first distance to the specific structure. Furthermore, a fusion distance to the specific structure is calculated as a product of the correction coefficient and the first distance to the specific structure, and travel control for the specific structure is executed based on the fusion distance.

[0011] Therefore, without requiring a second distance and fusion processing for the specific structure, the fusion distance to the specific structure can be calculated based on the first distance, and cruise control can be performed for the specific structure based on the fusion distance. Therefore, without requiring an expensive sensor such as LiDAR, the distance to the specific structure can be accurately detected and cruise control can be performed.

[0012] The "fusion distance" is a distance calculated based on the first distance and the second distance as the distance to the identified target by fusing the detection results of the camera sensor and the radar sensor to identify the target detected by both sensors. The fusion distance may be the same as the second distance, and the accuracy of the fusion distance is equal to or greater than the accuracy of the first distance and the accuracy of the second distance.

[0013] [Mode of the Invention] In one embodiment of the present invention, the particular structure (126) is a curb or a step between a roadway and a sidewalk.

[0014] According to the above aspect, in a situation where a curb on a road or a step between the roadway and the sidewalk is present in a specified area, driving control can be performed regarding the curb or step based on the fusion distance to the curb or step.

[0015] In another aspect of the present invention, the relationship is a relationship between a first distance (Lci) and a plurality of road surface gradients (φj) in the traveling direction of the vehicle, the road surface gradient, and a correction coefficient (Kij) that is determined in advance.

[0016] The coefficient for the first distance used to calculate the fusion distance based on the first distance varies depending on the gradient of the road surface in the traveling direction of the host vehicle. According to the above aspect, the relationship is a relationship between the first distance, the gradient of the road surface, and the correction coefficient, which is calculated in advance for multiple first distances and multiple gradients of the road surface in the traveling direction of the host vehicle. Therefore, the correction coefficient for calculating the fusion distance according to the gradient of the road surface in the traveling direction of the host vehicle can be calculated from the relationship.

[0017] Furthermore, in another aspect of the present invention, when the control unit (driving assistance ECU10) determines that a target measurable by the camera sensor and the radar sensor is present in a predetermined area and that a specific structure is present between the vehicle and the measurable target within the predetermined area (S40, S60), the control unit (driving assistance ECU10) is configured to: calculate a road surface gradient (φj) from the above relationship based on a first distance (Lci) to the measurable target and a ratio (Lfi / Lci) of the fusion distance to the first distance to the measurable target (S80); calculate a correction coefficient (Kij) from the above relationship based on the calculated road surface gradient and the first distance to the specific structure (S90); calculate a fusion distance (Lfi) to the specific structure as the product of the calculated correction coefficient and the first distance to the specific structure (S100); and execute driving control for the specific structure based on the fusion distance to the specific structure (S110).

[0018] According to the above aspect, when a specific structure is present within a predetermined area between the vehicle and a target measurable by the camera sensor and the radar sensor, the road surface gradient is calculated from the relationship based on the ratio of the first distance to the measurable target and the fusion distance. Furthermore, a correction coefficient is calculated from the relationship based on the road surface gradient and the first distance to the specific structure, and the fusion distance to the specific structure is calculated as the product of the correction coefficient and the first distance to the specific structure. Therefore, the correction coefficient for calculating the fusion distance to the specific structure can be calculated as a value corresponding to the road surface gradient, and thus the distance to the specific structure can be accurately detected and driving control can be performed without being affected by the road surface gradient.

[0019] In another aspect of the present invention, the target that can be measured is an obstacle on the sidewalk, including at least one of a pedestrian, a bicycle, and a wheelchair.

[0020] According to the above aspect, in a situation where there is an obstacle on the sidewalk, including at least one of a pedestrian, a bicycle, and a wheelchair, and a specific structure is between the vehicle and the obstacle, driving control can be performed regarding the specific structure, effectively reducing the risk of the vehicle colliding with the obstacle.

[0021] In the above description, to facilitate understanding of the present invention, the names and / or symbols used in the embodiments described below are enclosed in parentheses for the configurations of the invention corresponding to those embodiments. However, each component of the present invention is not limited to the components of the embodiments corresponding to the names and / or symbols enclosed in parentheses. Other objects, features, and attendant advantages of the present invention will be easily understood from the following description of the embodiments of the present invention, which will be given with reference to the drawings. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a schematic configuration diagram showing a driving control device according to an embodiment of the present invention; [Figure 2] 5 is a flowchart showing a travel control routine during skew in the first embodiment. [Figure 3] 10 is a flowchart showing a travel control routine during skew in a second embodiment. [Figure 4] 1 is a diagram showing a method for detecting the distance to a target using a monocular camera device of a camera sensor; [Figure 5] 10A and 10B are diagrams illustrating an example of travel control during slanting when an obstacle exists in a predetermined area but a specific structure does not exist in the predetermined area. [Figure 6] 10A and 10B are diagrams illustrating an example of travel control when the vehicle is traveling obliquely in a case where an obstacle and a specific structure are present in a predetermined area. DETAILED DESCRIPTION OF THE INVENTION

[0023] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A vehicle cruise control device according to an embodiment of the present invention will be described in detail below with reference to the accompanying drawings.

[0024] As shown in Fig. 1, a cruise control device 100 according to an embodiment of the present invention is applied to a vehicle 102 and includes a driving assistance ECU 10. The vehicle 102 is an autonomously driven vehicle and includes a drive ECU 20, a braking ECU 30, an electric power steering ECU 40, and a meter ECU 50. ECU refers to an electronic control unit that includes a microcomputer as its main component. In the following description, the electric power steering will be referred to as EPS.

[0025] The microcomputer of each ECU includes a CPU, ROM, RAM, read / write non-volatile memory (N / M), and an interface (I / F). The CPU performs various functions by executing instructions (programs, routines) stored in the ROM. Furthermore, these ECUs are interconnected via a Controller Area Network (CAN) 104 to enable data exchange (communication). Therefore, the detected values ​​of sensors (including switches) connected to a specific ECU are transmitted to other ECUs.

[0026] The driving assistance ECU 10 is a central control device that controls driving assistance such as collision avoidance control, driving control when the vehicle is traveling obliquely, etc. In this embodiment, the driving assistance ECU 10 cooperates with other ECUs to execute driving control when the vehicle is traveling obliquely, as will be described in detail later.

[0027] The driving assistance ECU 10 is connected to a camera sensor 12, a radar sensor 14, and a switch 16. The camera sensor 12 and the radar sensor 14 each include a plurality of camera devices and a plurality of radar devices. The camera sensor 12 and the radar sensor 14 function as a target information acquisition device 18 that acquires target information around the vehicle 102.

[0028] Although not shown, each camera device of camera sensor 12 includes a camera unit that captures images of the surroundings of vehicle 102 and a recognition unit that analyzes image data captured by the camera unit to recognize targets such as white lines on roads and other vehicles. The recognition unit supplies information about the recognized targets to driving assistance ECU 10 at predetermined time intervals. In particular, camera sensor 12 can measure the distance to the target as a first distance Lc, and supplies information about the first distance to driving assistance ECU 10 at predetermined time intervals.

[0029] The camera device of the camera sensor 12 may be either a compound-eye camera device or a monocular camera device, but in this embodiment, it is a monocular camera device. When the camera device is a monocular camera device, the distance from the camera device to the target is estimated by a method based on a pinhole camera model, as shown in Figure 4.

[0030] 4, there is a target 110 in front of the host vehicle 102, and the distance between the center of the lens (not shown) of the camera device of the camera sensor 12 and the target is Z, and the height of the center of the lens is H. In FIG. 4, for convenience of explanation, the imaging surface 112 is shown outside the camera device, but the distance corresponding to the height H of the imaging surface 112 inside the camera device is set to h, and the focal length of the lens is set to f.

[0031] The distance h can be detected, and the focal length f is a known value. A right triangle with sides of lengths f and h that form a 90° angle is similar to a right triangle with sides of lengths Z and H that form a 90° angle. Therefore, the distance Z can be calculated by f × H / h.

[0032] Each radar device of the radar sensor 14 uses millimeter-wave radio waves to detect the distance between the vehicle and a three-dimensional object, the relative speed between the vehicle and the three-dimensional object, the relative position (direction) of the three-dimensional object with respect to the vehicle, etc., and supplies information representing these to the driving assistance ECU 10 at predetermined time intervals. In particular, the radar sensor 14 can measure the distance to the target as a second distance Ll, and supplies information about the second distance to the driving assistance ECU 10 at predetermined time intervals. The accuracy of the second distance Ll is higher than the accuracy of the first distance Lc.

[0033] The driving assistance ECU 10 performs a fusion process on the detection results of the camera sensor 12 and the radar sensor 14 to identify a target detected by both sensors, and calculates a fusion distance Lf to the identified target based on the first distance Lc and the second distance Ll. Note that the fusion distance Lf may be the same as the second distance Ll, and the accuracy of the fusion distance Lf is equal to or greater than the accuracy of the first distance Lc and the accuracy of the second distance Ll.

[0034] The switch 16 is provided in a position that can be operated by the driver, such as on a steering wheel (not shown in Fig. 1), and is designed to be operated by the driver. The switch 16 includes a collision avoidance switch. When the collision avoidance switch is on, the driving assistance ECU 10 executes collision avoidance control and driving control when the vehicle is traveling obliquely.

[0035] The driving assistance ECU 10 determines whether or not an obstacle exists in a predetermined area in the traveling direction of the host vehicle 102 based on the detection results of the camera sensor 12 and the radar sensor 14. When the driving assistance ECU 10 determines that an obstacle exists, it executes collision avoidance control to avoid a collision between the host vehicle and the obstacle. Obstacles are obstacles to the traveling of the host vehicle, and include not only objects that would cause damage to the host vehicle if collided with, such as other vehicles or stationary objects, but also objects that would cause damage to the host vehicle if collided with, such as pedestrians.

[0036] As will be described in detail later, the driving assistance ECU 10 also determines whether the host vehicle 102 is traveling obliquely, i.e., whether the host vehicle 102 is traveling at an angle relative to the road, based on the detection results of the camera sensor 12 and the radar sensor 14. When the driving assistance ECU 10 determines that the host vehicle is traveling obliquely, it executes driving control for when the vehicle is traveling obliquely.

[0037] The drive ECU 20 is connected to a drive unit 22 that accelerates the vehicle 102 by applying drive force to drive wheels 24. The drive ECU 20 normally controls the drive unit 22 so that the drive force generated by the drive unit 22 changes in response to the driving operation by the driver, and when it receives a command signal from the driving assistance ECU 10, it controls the drive unit 22 based on the command signal. Thus, the drive ECU 20 and the drive unit 22 work together to function as a drive control device 26.

[0038] The braking ECU 30 is connected to a braking device 32 that applies braking force to wheels 34 to decelerate the vehicle 102. The braking ECU 30 normally controls the braking device so that the braking force generated by the braking device 32 changes in response to the braking operation by the driver, and when it receives a command signal from the driving assistance ECU 10, it controls the braking device 32 based on the command signal to perform automatic braking.

[0039] Therefore, the brake ECU 30 and the brake device 32 work together to function as a brake control device 36, which can control the braking force of the entire vehicle 102 and can also control the braking force of each wheel individually. When braking force is being applied to the wheels due to parking control or the like, brake lights (not shown in Fig. 1) are turned on.

[0040] An EPS device 42 is connected to the EPS-ECU 40. The EPS-ECU 40 controls the steering assist torque and reduces the steering burden on the driver by controlling the EPS device 42 in a manner known in the art based on the steering torque Ts and vehicle speed V detected by a driving operation sensor 60 and a vehicle state sensor 70, which will be described later. The EPS-ECU 40 also controls the EPS device 42 to steer the steered wheels 44 as needed. Therefore, the EPS-ECU 40 and the EPS device 42 function as a steering control device 46 that automatically steers the steered wheels as needed.

[0041] A touch panel display 52 that displays the status of control by the driving assistance ECU 10 and an alarm device 54 that issues alarms are connected to the meter ECU 50. The display 52 may be, for example, a multi-information display that displays meters and various information, or may be a display for a navigation device. The display 52 may be configured to display the status of collision avoidance control and driving control when the vehicle is swerving when receiving a signal from the driving assistance ECU 10.

[0042] The warning device 54 is activated when it is determined that the vehicle 102 is at risk of colliding with an obstacle, and issues a warning to the effect that a collision is imminent. The warning device 54 may be any of a warning device that issues a visual warning such as a warning lamp, a warning device that issues an auditory warning such as a warning buzzer, or a warning that issues a physical warning such as seat vibration, or any combination thereof.

[0043] The driving operation sensors 60 and the vehicle condition sensors 70 are also connected to the CAN 104. Information detected by the driving operation sensors 60 and the vehicle condition sensors 70 (referred to as sensor information) is transmitted to the CAN 104. The sensor information transmitted to the CAN 104 can be used appropriately in each ECU. Note that the sensor information may be information from a sensor connected to a specific ECU and transmitted to the CAN 104 from that specific ECU.

[0044] The driving operation sensor 60 includes a driving operation amount sensor that detects the amount of accelerator pedal operation, a braking operation amount sensor that detects the master cylinder pressure or the force applied to the brake pedal, a brake switch that detects whether the brake pedal is operated, a steering angle sensor that detects the steering angle, a steering torque sensor that detects the steering torque, etc.

[0045] The vehicle state sensor 70 includes a vehicle speed sensor that detects the speed of the vehicle 102, a longitudinal acceleration sensor that detects the longitudinal acceleration of the vehicle, a lateral acceleration sensor that detects the lateral acceleration of the vehicle, and a yaw rate sensor that detects the yaw rate of the vehicle.

[0046] [First embodiment] The ROM of the driving assistance ECU 10 stores a map of the relationship between a plurality of first distances Lci (i=1, 2...n, n is a positive integer) and a correction coefficient Ki for calculating the fusion distance Lfi based on the first distances Lci, as shown in Table 1 below. The correction coefficient Ki is a value calculated in advance for a plurality of first distances Lci when the host vehicle 102 is traveling on a horizontal, flat road. The correction coefficient Ki is, for example, the ratio Lfi / Lci of the fusion distance Lfi to the first distance Lci, and the fusion distance Lfi may be calculated as the product of the first distance Lci and the correction coefficient Ki. [Table 1]

[0047] When the driving assistance ECU 10 determines that an obstacle and a specific structure are present in a predetermined area and that the specific structure is located between the obstacle and the vehicle 102 while the vehicle 102 is traveling obliquely relative to the road, the driving assistance ECU 10 calculates a correction coefficient Ki from the relationship map shown in Table 1 based on the first distance Lci to the specific structure. Furthermore, the driving assistance ECU 10 calculates a fusion distance Lfi to the specific structure as the product of the calculated correction coefficient Ki and the first distance Lci to the specific structure, and performs driving control when traveling obliquely relative to the specific structure based on the calculated fusion distance Lfi.

[0048] In the first embodiment, the ROM of the driving assistance ECU 10 stores a program for controlling a traveling object when the vehicle is traveling obliquely, which program corresponds to the flowchart shown in FIG.

[0049] <Travel control when traveling skewed (Fig. 2)> Next, the travel control when the vehicle is traveling obliquely in the first embodiment will be described with reference to the flowchart shown in Fig. 2. The travel control when the vehicle is traveling obliquely according to the flowchart shown in Fig. 2 is repeatedly executed at predetermined time intervals by the CPU of the driving assistance ECU 10 when the collision avoidance switch of the switch 16 is on. In the following description, the travel control when the vehicle is traveling obliquely will be referred to as "main control."

[0050] First, in step S10, the CPU determines whether or not the host vehicle 102 is traveling obliquely with respect to the road, i.e., whether or not the host vehicle is traveling at an angle with respect to the lane, based on the information about the target object acquired by the target object information acquisition device 18. If a negative determination is made, this control is temporarily terminated, and if a positive determination is made, this control proceeds to step S20.

[0051] When a negative determination is made, normal driving control may be performed in any manner known in the art. For example, based on target information acquired by the target information acquisition device 18, it is determined whether or not there is an obstacle in a predetermined area ahead of the host vehicle 102, and when it is determined that there is an obstacle, a time to collision (TTC) is calculated. Furthermore, a target deceleration of the host vehicle is calculated based on the time to collision (TTC), and the drive control device 26 and the brake control device 36 are controlled so that the deceleration of the host vehicle becomes the target deceleration. Furthermore, the steering control device 46 may be controlled as necessary.

[0052] In step S20, the CPU determines whether or not there is a guardrail ahead of the vehicle 102 based on the information about the target object acquired by the target object information acquisition device 18. If a negative determination is made, the control proceeds to step S40, and if a positive determination is made, the control proceeds to step S30.

[0053] In step S30, the CPU executes a collision avoidance control for the guardrail when the vehicle is traveling obliquely. The collision avoidance control for the guardrail when the vehicle is traveling obliquely may be executed in any manner known in the art, such as the manner described in JP 2017-226393 A.

[0054] In step S40, the CPU determines whether or not there is an obstacle, including at least one of a pedestrian, a bicycle, and a wheelchair, in a predetermined area outside the roadway ahead of the vehicle 102, such as a sidewalk, based on the information about the target acquired by the target information acquisition device 18. If a positive determination is made, the control proceeds to step S60, and if a negative determination is made, the control proceeds to step S50.

[0055] In step S50, the CPU controls the drive control device 26 and the brake control device 36 to decelerate and stop the host vehicle 102 so that the host vehicle 102 does not deviate from the road as much as possible. Note that the steering control device 46 may also be controlled as necessary.

[0056] In step S60, the CPU determines whether or not there is a specific structure between the host vehicle and an obstacle in a predetermined area ahead of the host vehicle 102, based on the target information acquired by the target information acquisition device 18. If a positive determination is made, the control proceeds to step S90, and if a negative determination is made, the control proceeds to step S70.

[0057] In step S70, the CPU executes collision avoidance control for the obstacle. For example, a time to collision TTC for the obstacle is calculated, a target deceleration of the host vehicle is calculated based on the time to collision TTC, and the drive control device 26 and the brake control device 36 are controlled so that the deceleration of the host vehicle becomes the target deceleration. Note that the steering control device 46 may also be controlled as necessary.

[0058] In step S90, the CPU obtains a correction coefficient Ki from a map of the relationship shown in Table 1 based on the first distance Lci for the specific structure detected by the camera sensor 12. Note that when the first distance Lci is a value not found in the map, the correction coefficient Ki may be obtained from the map based on the value in the map that is closest to the first distance Lci. Alternatively, two correction coefficients Ki may be obtained from the map based on the two values ​​in the map that are closest to the first distance Lci, and the correction coefficient Ki corresponding to the first distance Lci may be obtained by proportional allocation.

[0059] In step S100, the CPU calculates the fusion distance Lfi to the specific structure as the product of the correction coefficient Ki and the first distance Lci.

[0060] In step S110, the CPU executes travel control for the specific structure when the vehicle is traveling obliquely based on the fusion distance Lfi. The travel control for the specific structure when the vehicle is traveling obliquely may be executed in any manner known in the art. For example, the control may be executed in the manner described in Japanese Patent Application Laid-Open No. 2017-226393.

[0061] 5 shows a situation in which the host vehicle 102 is traveling at an angle to the roadway 120, a pedestrian 122 is present as an obstacle in a predetermined area ahead of the host vehicle, and no specific structure exists between the host vehicle and the pedestrian. The pedestrian 122 is located on a sidewalk 124 outside the roadway 120, and there are no specific structures such as curbs or steps, or guardrails, between the roadway and the sidewalk.

[0062] In this situation, a positive determination is made in step S10, a negative determination is made in step S20, a positive determination is made in step S40, and a negative determination is made in step S60. Therefore, in step S70, collision avoidance control is executed for the pedestrian 122, and the host vehicle 102 is decelerated and stopped so as not to collide with the pedestrian 122.

[0063] 6 shows a situation in which the host vehicle 102 is traveling at an angle to the roadway 120, there is a pedestrian 122 as an obstacle in a predetermined area ahead of the host vehicle, and there is a curb 126 as a specific structure between the host vehicle and the pedestrian. There is no guardrail between the roadway and the sidewalk.

[0064] In this situation, a positive determination is made in step S10, a negative determination is made in step S20, and a positive determination is made in steps S40 and S60. Therefore, in step S90, a correction coefficient Ki is obtained from the relationship map shown in Table 1 based on the first distance Lc to the curb 126 detected by the camera sensor 12. Furthermore, in step S100, a fusion distance Lfi to the curb 126 is calculated as the product of the correction coefficient Ki and the first distance Lc, and in step S110, travel control is executed when the vehicle is traveling skewed around the curb 126.

[0065] Because the fusion distance Lfi is more accurate than the first distance Lc, cruise control can be performed more effectively than when cruise control is performed based on the first distance Lc. Therefore, the host vehicle 102 can be automatically decelerated so that the driver can steer the host vehicle 102 to change direction without colliding with or climbing over the curb 126, and the risk of the host vehicle colliding with the pedestrian 122 can be effectively reduced.

[0066] [Second embodiment] In the second embodiment, the ROM of the driving assistance ECU 10 stores a map of the relationship between a plurality of first distances Lci (i = 1, 2 ... n, n is a positive integer), a plurality of road surface gradients φj (j = 1, 2 ... m, m is a positive integer), and a correction coefficient Kij, as shown in Figure 2 below. The correction coefficient Kij is a value calculated in advance for the plurality of first distances Lci and the plurality of road surface gradients φj as a correction coefficient for calculating a corresponding fusion distance Lfi based on the first distance Lci. The road surface gradient φj is the gradient of the road surface in the traveling direction of the host vehicle. In the second embodiment, the correction coefficient Kij may also be a correction coefficient for the first distance Lci for calculating the fusion distance Lfi, for example, Lfi / Lci, which is the ratio of the fusion distance Lfi to the first distance Lci. Note that the smaller the value of j, the greater the downhill gradient of the road surface gradient φj, and the greater the value of j, the greater the uphill gradient, with the intermediate gradient being zero. [Table 2]

[0067] When the driving assistance ECU 10 determines that an obstacle and a specific structure are present in a predetermined area and that the specific structure is located between the obstacle and the vehicle 102 while the vehicle 102 is traveling obliquely relative to the road, the driving assistance ECU 10 calculates a fusion distance Lfi to the obstacle. The fusion distance Lfi to the obstacle is calculated based on a first distance Lci and a second distance Lli to the obstacle in a manner known in the art. The driving assistance ECU 10 calculates the ratio Lfi / Lci of the fusion distance Lfi to the first distance Lci, determines a correction coefficient Ki closest to the ratio Lfi / Lci from the correction coefficients Ki in the relationship map shown in Table 2, and determines the road surface gradient φj corresponding to the determined correction coefficient Ki.

[0068] The driving assist ECU 10 calculates a correction coefficient Kij from the map of the relationship shown in Table 2 based on the first distance Lci to the specific structure and the determined road surface gradient φj. Furthermore, the driving assist ECU 10 calculates a fusion distance Lfi to the specific structure as the product of the calculated correction coefficient Kij and the first distance Lci to the specific structure, and performs driving control when the vehicle is traveling obliquely around the specific structure based on the calculated fusion distance Lfi.

[0069] In the second embodiment, the ROM of the driving assistance ECU 10 stores a program for travel control during skewing, which program corresponds to the flowchart shown in FIG.

[0070] <Travel control when traveling skewed (Fig. 3)> The travel control when the vehicle is traveling obliquely according to the flowchart shown in FIG. 3 is also repeatedly executed at predetermined time intervals by the CPU of the driving assistance ECU 10 while the collision avoidance switch of the switch 16 is on.

[0071] As can be seen from a comparison between FIG. 3 and FIG. 2, steps other than steps S80 to S100 are executed in the same manner as in the first embodiment, and step S80 is executed when a positive determination is made in step S60.

[0072] In step S80, the CPU calculates a fusion distance Lfi to the obstacle based on the first distance Lci and the second distance Lli detected by the camera sensor 12 and the radar sensor 14, respectively. The CPU calculates the ratio Lfi / Lci of the fusion distance Lfi to the first distance Lci, determines the correction coefficient Kij closest to the ratio Lfi / Lci among the correction coefficients Kij in the relationship map shown in Table 2, and determines the road gradient φj corresponding to the determined correction coefficient Kij.

[0073] In step S90, the CPU obtains a correction coefficient Kij from the relationship map shown in Table 2 based on the first distance Lci for the specific structure and the gradient φj of the road surface.

[0074] Furthermore, in step S100, the CPU calculates a fusion distance Lfi to the specific structure as the product of the correction coefficient Ki and the first distance Lci to the specific structure. Then, in step S110, travel control is executed for the specific structure when the vehicle is traveling obliquely based on the fusion distance Lfi.

[0075] As can be seen from the above explanation, according to the first and second embodiments, the correction coefficient Ki or Kij is calculated based on the first distance to the specific structure from the relationship in Table 1 or Table 2. Furthermore, the fusion distance Lfi to the specific structure is calculated as the product of the correction coefficient and the first distance Lci to the specific structure, and travel control is executed for the specific structure based on the fusion distance.

[0076] Therefore, without requiring a second distance and fusion processing for the specific structure, the fusion distance to the specific structure can be calculated based on the first distance, and cruise control can be performed for the specific structure based on the fusion distance. Therefore, without requiring an expensive sensor such as LiDAR, the distance to the specific structure can be accurately detected and cruise control can be performed.

[0077] In particular, according to the second embodiment, the relationship in Table 2 is a relationship between the first distances, the road surface gradients, and the correction coefficients Kij, which are calculated in advance for a plurality of first distances Lci and a plurality of road surface gradients φj in the traveling direction of the host vehicle. Therefore, the correction coefficients Kij for calculating the fusion distance according to the road surface gradients in the traveling direction of the host vehicle 102 can be calculated from the relationship in Table 2.

[0078] Furthermore, according to the second embodiment, the road surface gradient φj is calculated from the relationship in Table 2 based on the ratio of the fusion distance to the first distance for the measurable target. Furthermore, a correction coefficient Kij is calculated from the relationship in Table 2 based on the road surface gradient and the first distance Lci for the specific structure, and the fusion distance Lfi to the specific structure is calculated as the product of the correction coefficient and the first distance for the specific structure. Therefore, the correction coefficient for calculating the fusion distance can be calculated as a value corresponding to the road surface gradient in the traveling direction of the host vehicle, and this makes it possible to accurately detect the distance to the specific structure and perform cruise control without being affected by the road surface gradient.

[0079] Although the present invention has been described in detail above with reference to specific embodiments, it will be apparent to those skilled in the art that the present invention is not limited to the above-described embodiments, and that various other embodiments are possible within the scope of the present invention.

[0080] For example, in the first and second embodiments described above, the cruise control for a specific structure based on the fusion distance to the specific structure is executed when the host vehicle is traveling obliquely. However, the cruise control may be executed when the host vehicle is traveling in a direction other than obliquely.

[0081] In the first and second embodiments, the measurable targets are obstacles on the sidewalk that include at least one of a pedestrian, a bicycle, and a wheelchair. However, the measurable targets may be obstacles on the sidewalk other than a pedestrian, a bicycle, and a wheelchair.

[0082] Furthermore, in the first and second embodiments described above, if it is determined in step S60 that there is no specific structure between the vehicle and the obstacle, step S70 is executed. However, if a white line that is a boundary between the lanes is detected, control similar to the driving control for the specific structure may be performed based on the white line. [Explanation of symbols]

[0083] 10... driving assistance ECU, 12... camera sensor, 14... radar sensor, 18... target information acquisition device, 22... drive device, 32... braking device, 50... meter ECU, 100... cruise control device, 102... vehicle, 122... pedestrian, 126... curb

Claims

1. A vehicle cruise control device including a camera sensor and a radar sensor capable of measuring a distance to a target as a first distance and a second distance, respectively, and a control unit that, when it is determined that an obstacle exists in a predetermined area in the traveling direction of the vehicle based on detection results of the camera sensor and the radar sensor, executes cruise control to reduce the risk of collision between the vehicle and the obstacle, the control unit stores a relationship between a first distance and a correction coefficient, the relationship being determined in advance for a plurality of first distances, the correction coefficient being a coefficient for the first distance for determining a fusion distance based on the first distance and the second distance, A vehicle driving control device configured such that, when the control unit determines that a specific structure is present in the specified area, the control unit calculates a correction coefficient from the relationship based on the first distance to the specific structure, calculates a fusion distance to the specific structure as the product of the calculated correction coefficient and the first distance to the specific structure, and performs the driving control for the specific structure based on the calculated fusion distance to the specific structure.

2. 2. The vehicle travel control device according to claim 1, wherein the specific structure is a curb of a road or a step between a roadway and a sidewalk.

3. 3. The vehicle driving control device according to claim 1, wherein the relationship is a relationship between the first distance, the road surface gradient, and the correction coefficient, the relationship being determined in advance for a plurality of first distances and a plurality of road surface gradients in the direction of travel of the vehicle.

4. 4. The vehicle driving control device according to claim 3, wherein the control unit is configured to, when it determines that a target measurable by the camera sensor and the radar sensor is present in the predetermined area and that the specific structure is present between the vehicle and the measurable target within the predetermined area, calculate a road surface gradient from the relationship based on the first distance to the measurable target and a ratio of the fusion distance to the first distance to the measurable target, calculate a correction coefficient from the relationship based on the calculated road surface gradient and the first distance to the specific structure, calculate a fusion distance to the specific structure as the product of the calculated correction coefficient and the first distance to the specific structure, and execute the driving control for the specific structure based on the fusion distance to the specific structure.

5. 5. The vehicle travel control device according to claim 4, wherein the target object whose distance can be measured is an obstacle on a sidewalk, the obstacle including at least one of a pedestrian, a bicycle, and a wheelchair.

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