Vehicle driving assistance device

Abstract

To provide a driving support device for a vehicle that can perform driving control to avoid obstacles, etc. that exist ahead of the vehicle on the roadway more accurately at an earlier timing.SOLUTION: A driving support device for a vehicle includes: ambient environment recognition devices 11 and 37 that recognize the surrounding environment of a vehicle; an obstacle estimation unit that performs overall control of the vehicle and also estimates the existence of obstacles ahead based on the behavior distribution of a plurality of preceding vehicles recognized by the ambient environment recognition devices, and estimates the position and area in which the obstacles exist; a travel path calculation unit that calculates a plurality of candidate travel path regions for the vehicle to travel in order to avoid the estimated obstacles; and a travel path selection unit 14 that selects and sets an appropriate travel path region from the plurality of calculated travel path regions, and controls the driving of the vehicle along the set travel path region.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a driving assistance device for a vehicle that performs driving assistance control based on surrounding environment information acquired using an on-board camera device, an on-board radar device, or the like. [Background technology]

[0002] In recent years, development of automatic driving control technology for vehicles such as automobiles that allows the vehicle to travel automatically without the need for driver operation has been progressing. In addition, various driving assistance devices that can perform various driving controls to assist the driver in driving operations using this type of automatic driving control technology have been proposed and are becoming generally put into practical use.

[0003] In conventional driving assistance systems, sensing devices such as an in-vehicle camera device or an in-vehicle radar device are used as a surrounding environment recognition device for recognizing the surrounding environment of the vehicle and acquiring the surrounding information.

[0004] For example, the above-mentioned vehicle-mounted camera device acquires image data and, based on the acquired image data, recognizes the vehicle's surrounding environment, such as road markings (hereinafter simply referred to as road markings, etc.), as well as various three-dimensional objects present on the road (such as road curbs, guardrails, pedestrians, bicycles, other vehicles, and other obstacles that may obstruct the vehicle's movement).

[0005] In addition, the above-mentioned vehicle-mounted radar device outputs radio waves toward the surroundings of the vehicle, receives reflected waves from objects, and analyzes the received waves to recognize various three-dimensional objects (same as above) present around the vehicle.

[0006] Conventional driving assistance devices are known to have control technology that, when the vehicle is traveling while using these sensing devices to recognize the surrounding environment, if an obstacle or the like that may impede the vehicle's travel is recognized on the vehicle's path, the obstacle or the like is avoided and the vehicle continues traveling safely.

[0007] However, with only such control technology, obstacle avoidance control is initiated from the moment an obstacle or the like is recognized by the vehicle's sensing device, which may leave little time to perform the avoidance operation. For example, when a leading vehicle is traveling immediately in front of the vehicle, it may be difficult for the vehicle to recognize an obstacle or the like in front of the leading vehicle. In such a case, the timing at which the vehicle's driving assistance device recognizes the obstacle or the like is delayed. In this case, control such as sudden steering or sudden braking is performed in order to avoid the obstacle or the like. If such driving control is performed, there is a possibility that the driver may feel uneasy.

[0008] Therefore, in conventional driving assistance devices, in addition to the normal obstacle avoidance control that is performed by directly recognizing obstacles, etc., as described above, various control technologies that avoid obstacles, etc. based on the behavior of a preceding vehicle have been proposed, for example, in Patent Publication No. 2018-171959, Patent Publication No. 2017-13678, etc.

[0009] The driving assistance device disclosed in the above-mentioned JP 2018-171959 A and the like is designed to detect the preceding vehicle's obstacle avoidance behavior early, thereby speeding up the timing at which the vehicle starts obstacle avoidance behavior.

[0010] In addition, the driving assistance device disclosed in the above-mentioned JP 2017-13678 A and the like is configured to, when a leading vehicle avoids an obstacle, perform obstacle avoidance for the vehicle along the same driving route as the leading vehicle. [Prior art documents] [Patent documents]

[0011] [Patent Document 1] Japanese Patent Application Publication No. 2018-171959 [Patent Document 2] Japanese Patent Application Publication No. 2017-13678 Summary of the Invention [Problem to be solved by the invention]

[0012] However, in conventional driving assistance devices disclosed in the above-mentioned Japanese Patent Application Laid-Open No. 2018-171959 and Japanese Patent Application Laid-Open No. 2017-13678, the presence of an obstacle or the like is determined based only on the behavior of a preceding vehicle traveling immediately in front of the vehicle. With such control, it is difficult to determine, for example, whether the preceding vehicle is taking a behavior intended to avoid an obstacle or is simply traveling in a zigzag manner. Therefore, conventional control has a problem in that it is difficult to consistently make highly reliable determinations.

[0013] The present invention aims to provide a vehicle driving assistance device that can start obstacle avoidance control at an earlier timing and perform more accurate obstacle avoidance control when an obstacle or the like that may hinder the travel of a traveling vehicle is present on the path of the traveling vehicle. [Means for solving the problem]

[0014] In order to achieve the above object, a driving assistance device for a vehicle according to one aspect of the present invention is a driving assistance device for a vehicle that can perform at least lane keeping control for driving a vehicle along a driving lane, and obstacle avoidance control for setting a driving route that avoids obstacles on a road and driving the vehicle along the driving route, the driving assistance device comprising: a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; before The surrounding environment recognition device recognizes the behavior distribution of the preceding vehicles based on the behavior distribution of the preceding vehicles. The aforementioned an obstacle estimation unit that estimates the presence of an obstacle and, if the presence of the obstacle is estimated, estimates the position and area where the obstacle exists; and a path calculation unit that calculates a plurality of candidate path areas for the vehicle to travel while avoiding the estimated obstacle; calculation Served The aforementioned a route selection unit that selects and sets an appropriate route area from a plurality of route areas, The aforementioneda travel control unit for controlling travel of the vehicle along a travel path region; The plurality of preceding vehicles are at least two preceding vehicles traveling on the same lane as the vehicle, and the behavior distribution is calculated based on the amount of change in lateral position when the at least two preceding vehicles deviate laterally from a virtual center line of the traveling lane. . [Effects of the Invention]

[0015] According to the present invention, it is possible to provide a vehicle driving assistance device that can start obstacle avoidance control at an earlier timing and perform more accurate obstacle avoidance control when an obstacle or the like that may hinder the vehicle's travel is present on the path of the vehicle while it is traveling. [Brief explanation of the drawings]

[0016] [Figure 1] FIG. 1 is a block diagram showing a schematic configuration of a driving assistance device according to an embodiment of the present invention; [Figure 2] 1 is a conceptual diagram showing an example of a situation in which a vehicle equipped with a driving assistance device according to an embodiment of the present invention is traveling on a road in a driving assistance mode; [Figure 3] FIG. 1 is a conceptual diagram showing another example of a situation in which a vehicle equipped with a driving assistance device according to an embodiment of the present invention is traveling on a road in a driving assistance mode; [Figure 4] 1 is a flowchart showing the operation of a driving assistance device according to an embodiment of the present invention; [Figure 5] FIG. 5 is a diagram conceptually showing a plurality of candidate routes calculated in the processing of step S16 of FIG. [Figure 6] FIG. 5 is a conceptual diagram illustrating a situation in which the position of the selected route candidate area is adjusted based on the surrounding environment during the driving control executed in step S16 of FIG. [Figure 7] A flowchart showing a subroutine of a modified example of the route candidate selection process (the process of step S17 in FIG. 4) in one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0017] The present invention will be described below with reference to the illustrated embodiments. The drawings used in the following description are schematic, and the dimensional relationships and scales of the components may be different for each component in order to show each component at a size that allows it to be recognized on the drawing. Therefore, the present invention is not limited to the illustrated embodiments in terms of the number of components shown in the drawings, the shapes of the components, the size ratios of the components, the relative positional relationships of the components, and so on.

[0018] In explaining the configuration and operation of this embodiment, the road system is based on left-hand traffic, with the lane for vehicles facing the direction of travel being on the left. Therefore, to apply the configuration of the present invention to a road system based on right-hand traffic, it can be easily applied by simply switching the left and right.

[0019] First, a schematic configuration of a driving assistance device according to one embodiment of the present invention will be described below with reference to Fig. 1. Fig. 1 is a block diagram showing a schematic configuration of a driving assistance device according to one embodiment of the present invention. As shown in Fig. 1, the basic configuration of the driving assistance device 1 according to this embodiment is substantially the same as that of a conventional driving assistance device of this type. Therefore, the following description will be limited to a schematic description of the driving assistance device 1 according to this embodiment.

[0020] The driving assistance device 1 of this embodiment has a camera unit 10, which is an in-vehicle camera device fixed to the front upper center part of the interior of the vehicle (hereinafter referred to as the host vehicle) in which the driving assistance device 1 is mounted.

[0021] The camera unit 10 includes a stereo camera 11, an image processing unit (IPU) 12, an image recognition unit (image recognition_ECU) 13, and a driving control unit (driving_ECU) 14.

[0022] The stereo camera 11 has a main camera 11a and a sub-camera 11b. The main camera 11a and the sub-camera 11b are arranged, for example, in the cabin of the vehicle at symmetrical positions across the center of the vehicle width direction, facing forward (in the direction of travel). The main camera 11a and the sub-camera 11b are configured, for example, with CMOS image sensors, and generate a stereo image by capturing two images of the surrounding environment of a predetermined range of an area in front of the vehicle from different viewpoints at a predetermined imaging period that is synchronized with each other.

[0023] IPU 12 performs predetermined image processing on the surrounding environment image data (image data representing the surrounding environment while the vehicle is traveling) captured by stereo camera 11, and detects the edges of various objects such as objects shown in the image and lane markings (hereinafter simply referred to as lane markings, etc.) marked on the road surface. In this way, IPU 12 recognizes three-dimensional objects, lane markings, etc. around the vehicle. IPU 12 then obtains distance information from the amount of positional deviation of corresponding edges on the left and right images, and generates image information including the distance information (distance image information).

[0024] Based on distance image information received from the IPU 12, the image recognition ECU 13 calculates the road curvature [1 / m] of the marking lines dividing the left and right sides of the roadway on which the vehicle is traveling (the host vehicle roadway) and the width between the left and right marking lines (lane width). Various methods are known for calculating the road curvature and lane width. For example, the image recognition ECU 13 recognizes the left and right marking lines by binarizing the road curvature based on the surrounding environment information using brightness differences, and calculates the curvatures of the left and right marking lines for each predetermined section using a curve approximation formula based on the least squares method. Furthermore, the image recognition ECU 13 calculates the lane width from the difference in curvature between the left and right marking lines.

[0025] Then, the image recognition_ECU 13 calculates the lane center, the lateral position deviation of the vehicle, which is the distance from the lane center to the center of the vehicle in the vehicle width direction, and the like, based on the curvature of the left and right lane markings and the lane width.

[0026] Furthermore, the image recognition_ECU 13 performs predetermined pattern matching on the distance image information to recognize three-dimensional objects such as guardrails extending along the road, curbs, and surrounding vehicles. Here, the recognition of three-dimensional objects by the image recognition_ECU 13 recognizes, for example, the type of the three-dimensional object, the height of the three-dimensional object, the distance to the three-dimensional object, the speed of the three-dimensional object, the relative speed between the three-dimensional object and the vehicle, and the relative distance between three-dimensional objects (for example, the lateral distance between a curb at the edge of the road and a dividing line nearby).

[0027] The various pieces of information recognized by the image recognition_ECU 13 are output to the traveling_ECU 14 as first surrounding environment information.

[0028] In this manner, in this embodiment, the image recognition_ECU 13, together with the stereo camera 11 and the IPU 12, realizes the function of a surrounding environment recognition device that recognizes the first surrounding environment around the vehicle.

[0029] The travel_ECU 14 is a control unit for overall control of the driving assistance device 1. Various control units, such as a cockpit control unit (CP_ECU) 21, an engine control unit (E / G_ECU) 22, a transmission control unit (T / M_ECU) 23, a brake control unit (BK_ECU) 24, and a power steering control unit (PS_ECU) 25, are connected to the travel_ECU 14 via an in-vehicle communication line such as a CAN (Controller Area Network).

[0030] Furthermore, various sensors, such as a locator unit 36, an on-board radar device 37 (left front side sensor 37lf, right front side sensor 37rf, left rear side sensor 37lr, right rear side sensor 37rr), and a rear sensor 38, are connected to the travel_ECU 14.

[0031] A human-machine interface (HMI) 31, which is arranged near the driver's seat, is connected to the CP_ECU 21. The HMI 31 is configured to include, for example, a switch for issuing an instruction to execute various driving assistance controls, a mode selector switch for switching driving modes, a steering touch sensor for detecting the driver's steering state, a driver monitoring system (DMS) for detecting the driver's facial recognition and line of sight, a touch panel display, a combination meter, a speaker, and the like.

[0032] When the CP_ECU 21 receives a control signal from the travel_ECU 14, it notifies the driver of various warnings for preceding vehicles, the implementation status of driving assistance controls, and various information related to the surrounding environment of the vehicle, etc., as appropriate, by display, audio, etc. via the HMI 31. In addition, the CP_ECU 21 outputs various input information, such as the on / off operation status of various driving assistance controls input by the driver via the HMI 31, to the travel_ECU 14.

[0033] The output side of the E / G_ECU 22 is connected to a throttle actuator 32 of an electronically controlled throttle, etc. The input side of the E / G_ECU 22 is connected to various sensors such as an accelerator sensor (not shown).

[0034] The E / G_ECU 22 controls the operation of the throttle actuator 32 based on a control signal from the travel_ECU 14 or detection signals from various sensors. In this way, the E / G_ECU 22 adjusts the amount of intake air into the engine to generate a desired engine output. The E / G_ECU 22 also outputs signals such as the accelerator opening detected by the various sensors to the travel_ECU 14.

[0035] An output side of the T / M_ECU 23 is connected to a hydraulic control circuit 33. Furthermore, various sensors such as a shift position sensor (not shown) are connected to an input side of the T / M_ECU 23. The T / M_ECU 23 performs hydraulic control for the hydraulic control circuit 33 based on an engine torque signal estimated by the E / G_ECU 22 and detection signals from various sensors. As a result, the T / M_ECU 23 operates friction engagement elements, pulleys, and the like provided in the automatic transmission, and shifts the engine output at a desired gear ratio. Furthermore, the T / M_ECU 23 outputs signals such as the shift position detected by the various sensors to the travel_ECU 14.

[0036] A brake actuator 34 for adjusting the brake fluid pressure output to the brake wheel cylinders provided on the respective wheels is connected to the output side of the BK_ECU 24. In addition, various sensors such as a brake pedal sensor, a yaw rate sensor, a longitudinal acceleration sensor, and a vehicle speed sensor (not shown) are connected to the input side of the BK_ECU 24.

[0037] The BK_ECU 24 controls the driving of the brake actuator 34 based on control signals from the travel_ECU 14 or detection signals from various sensors. As a result, the BK_ECU 24 appropriately generates braking force on each wheel to perform forced braking control on the host vehicle, yaw rate control, etc. The BK_ECU 24 also outputs signals to the travel_ECU 14 indicating the brake operation state, yaw rate, longitudinal acceleration, vehicle speed (host vehicle speed), etc., detected by various sensors.

[0038] An electric power steering motor 35, which applies steering torque to the steering mechanism by the rotational force of the motor, is connected to the output side of the PS_ECU 25. In addition, various sensors such as a steering torque sensor and a steering angle sensor are connected to the input side of the PS_ECU 25.

[0039] The PS_ECU 25 controls the drive of the electric power steering motor 35 based on control signals from the travel_ECU 14 or detection signals from various sensors. As a result, the PS_ECU 25 generates a steering torque for the steering mechanism. The PS_ECU 25 also outputs signals of the steering torque, steering angle, etc. detected by the various sensors to the travel_ECU 14.

[0040] The locator unit 36 ​​includes a GNSS sensor 36a and a high-precision road map database (road map DB) 36b.

[0041] The GNSS sensor 36a receives positioning signals transmitted from a plurality of positioning satellites to determine the position (latitude, longitude, altitude, etc.) of the vehicle.

[0042] The road map DB 36b is a large-capacity storage medium such as an HDD or SSD, and stores high-precision road map information (dynamic map). The road map DB 36b stores lane data required for autonomous driving, such as lane width data, lane center position coordinate data, lane travel azimuth data, and speed limits. This lane data is stored at intervals of several meters for each lane on the road map. The road map DB also stores information on various facilities, parking lots, and the like. For example, based on a request signal from the traveling_ECU 14, the road map DB 36b outputs road map information of a set range based on the vehicle position measured by the GNSS sensor 36a to the traveling_ECU 14 as third surrounding environment information.

[0043] In this way, in this embodiment, the road map DB 36b, together with the GNSS sensor 36a, realizes the function of a surrounding environment recognition device that recognizes the third surrounding environment around the vehicle.

[0044] The left front side sensor 37lf, the right front side sensor 37rf, the left rear side sensor 37lr, and the right rear side sensor 37rr are a plurality of sensors that constitute the on-vehicle radar device 37, and are configured by, for example, millimeter wave radars.

[0045] Here, each millimeter-wave radar receives and analyzes the reflected waves from objects in response to the emitted radio waves, thereby detecting mainly three-dimensional objects such as pedestrians and vehicles traveling alongside, as well as structures (e.g., curbs, guardrails, walls of buildings, plants, and other three-dimensional objects) installed on the edge of the road (e.g., the edge of the shoulder). Furthermore, each millimeter-wave radar also detects three-dimensional obstacles present on the road. In this case, each radar detects specific information about the three-dimensional object, such as the width of the three-dimensional object, the position of its representative point (relative position and distance to the vehicle), and the relative speed.

[0046] The left front side sensor 37lf and the right front side sensor 37rf are disposed, for example, on the left and right sides of the front bumper, respectively. The left front side sensor 37lf and the right front side sensor 37rf detect, as second surrounding environment information, three-dimensional objects present in areas diagonally forward and to the left and right and to the sides of the vehicle, which are difficult to recognize in the image from the stereo camera 11.

[0047] The left rear side sensor 37lr and the right rear side sensor 37rr are disposed, for example, on the left and right sides of the rear bumper, respectively. The left rear side sensor 37lr and the right rear side sensor 37rr detect, as second surrounding environment information, three-dimensional objects present in areas diagonally to the left and right sides and rear of the vehicle that are difficult to recognize with the left front side sensor 37lf and the right front side sensor 37rf.

[0048] In this manner, in this embodiment, the on-board radar device 37 (the front side sensor 37lf, the right front side sensor 37rf, the left rear side sensor 37lr, and the right rear side sensor 37rr) functions as a surrounding environment recognition device that recognizes the second surrounding environment around the vehicle. The information acquired by these sensors 37lf, 37rf, 37lr, and 37rr is sent to the image recognition_ECU 13.

[0049] The rear sensor 38 is configured by, for example, a sonar device, etc. The rear sensor 38 is disposed, for example, on the rear bumper. The rear sensor 38 detects, as the fourth surrounding environment information, three-dimensional objects present in the area behind the vehicle that are difficult to recognize with the left rear side sensor 37lr and the right rear side sensor 37rr.

[0050] In this way, in this embodiment, the rear sensor 38 functions as a surrounding environment recognition device that recognizes the fourth surrounding environment around the vehicle.

[0051] In addition, the coordinates of each object outside the vehicle included in the first surrounding environment information recognized by the image recognition_ECU 13, the third surrounding environment information recognized by the locator unit 36, the second surrounding environment information recognized by the on-board radar device 37 (left front side sensor 37lf, right front side sensor 37rf, left rear side sensor 37lr, right rear side sensor 37rr), and the fourth surrounding environment information recognized by the rear sensor 38 are all converted by the driving_ECU 14 into coordinates of a three-dimensional coordinate system with the center of the vehicle as the origin.

[0052] The driving modes set in the travel_ECU 14 include a manual driving mode, a first driving control mode and a second driving control mode for driving control, and an evacuation mode. These driving modes can be selectively switched in the travel_ECU 14 based on, for example, the operation status of a mode selector switch provided in the HMI 31.

[0053] Here, manual driving mode is a driving mode that requires the driver to maintain steering, and is a driving mode in which the vehicle is driven according to driving operations such as steering, accelerator, and brake operations by the driver.

[0054] Similarly, the first driving control mode is a driving mode that requires the driver to maintain steering. That is, the first driving control mode is a so-called semi-automated driving mode or a driving assistance mode in which the vehicle is driven along a target driving route by appropriately combining mainly adaptive cruise control (ACC), active lane keep centering (ALKC), and active lane keep bouncing (ALKC) controls through control of the E / G_ECU 22, BK_ECU 24, PS_ECU 25, etc., while reflecting the driving operation by the driver.

[0055] Here, the adaptive cruise control (ACC) is basically performed based on the first ambient environment information input from the image recognition ECU 13. That is, the adaptive cruise control (ACC) is performed based on, for example, the preceding vehicle information included in the first ambient environment information from the image recognition ECU 13.

[0056] Furthermore, the lane centering control and lane departure prevention control are basically performed based on the first and third surrounding environment information input from at least one of the image recognition_ECU 13 and the locator unit 36. That is, the lane centering control and lane departure prevention control are performed based on, for example, lane marking information included in the third surrounding environment information from the image recognition_ECU 13 or the locator unit 36.

[0057] The second driving control mode is an autonomous driving mode that realizes a so-called hands-off function in which the vehicle travels along a target route (route map information) without the driver needing to maintain steering, operate the accelerator, or operate the brakes, by appropriately combining mainly preceding vehicle following control, lane centering control, and lane departure prevention control through control of, for example, the E / G_ECU22, BK_ECU24, PS_ECU25, etc.

[0058] The evacuation mode is a mode for automatically stopping the vehicle on a roadside or the like when, for example, while driving in the second driving control mode, driving in that mode cannot be continued and the driver is unable to take over driving operations (i.e., when the vehicle cannot transition to manual driving mode or the first driving control mode).

[0059] In addition, in each of the above-mentioned driving modes, when the traveling_ECU14 recognizes an obstacle such as a preceding vehicle on the vehicle's driving path that is likely to collide with the vehicle or a three-dimensional object such as a fallen object, the traveling_ECU14 executes obstacle avoidance control accompanied by emergency braking (AEB (Autonomous Emergency Braking): collision damage mitigation brake) control and emergency steering control as appropriate and necessary.

[0060] All or part of the locator unit 36, image recognition_ECU 13, driving_ECU 14, CP_ECU 21, E / G_ECU 22, T / M_ECU 23, BK_ECU 24, PS_ECU 25, etc. are configured by a processor including hardware.

[0061] Here, the processor is configured by a well-known configuration including, for example, a central processing unit (CPU), a random access memory (RAM), a read-only memory (ROM), a non-volatile memory, a non-volatile storage, a non-transitory computer readable medium, and peripheral devices thereof.

[0062] Software programs to be executed by the CPU, fixed data such as data tables, etc. are stored in advance in ROM, nonvolatile memory, nonvolatile storage devices, etc. Then, the CPU reads out the software programs stored in ROM, etc., expands them into RAM, and executes them, and the software programs appropriately refer to various data, etc., thereby realizing the functions of the above-mentioned components and components units (13, 14, 21 to 25, 36), etc.

[0063] The processor may be configured with a semiconductor chip such as a Field Programmable Gate Array (FPGA), etc. The above components and component units (13, 14, 21 to 25, 36) may be configured with electronic circuits.

[0064] Furthermore, the software program may be in a form in which it is recorded in whole or in part as a computer program product on a portable disk medium such as a flexible disk, CD-ROM, or DVD-ROM, or on a non-transitory computer readable medium such as a card-type memory, HDD (Hard Disk Drive) device, or SSD (Solid State Drive) device.

[0065] The operation of the driving support device 1 of this embodiment configured as above will be described below with reference to FIGS.

[0066] As described above, the driving assistance device 1 of this embodiment has a function to assist the driver in driving operations by executing so-called adaptive cruise control (ACC), lane centering control (ALKC), lane departure prevention control (ALKB), etc. Furthermore, the driving assistance device 1 of this embodiment has a function to assist driving by executing obstacle avoidance control when an obstacle or the like is recognized on the road during driving.

[0067] Furthermore, even when a vehicle equipped with the driving assistance device 1 is traveling on a road in driving assistance mode and is unable to directly recognize an obstacle or the like ahead of the vehicle's path of travel, the driving assistance device 1 of this embodiment has the function of recognizing the behavior of multiple preceding vehicles to estimate the presence or absence, position, size, etc. of an obstacle or the like ahead of the vehicle's path of travel (area where the obstacle or the like exists), and executing obstacle avoidance control before directly recognizing the obstacle or the like.

[0068] For example, FIGS. 2 and 3 are conceptual diagrams showing a situation in which a vehicle equipped with the driving assistance device 1 of this embodiment is traveling on a road in driving assistance mode.

[0069] First, a brief description will be given of the situation shown in Fig. 2. In Fig. 2, the symbol M indicates the host vehicle. As shown in Fig. 2, the host vehicle M is traveling in the center lane of a road with three lanes in each direction.

[0070] Here, reference numeral 100 in FIG. 2 indicates the roadway on which the host vehicle M is traveling. Reference numeral 101 of the roadway 100 indicates the host vehicle lane on which the host vehicle M is traveling. Reference numeral 101L indicates the left lane adjacent to the left side of the host vehicle lane 101. Reference numeral 101R indicates the right lane (a so-called passing lane) adjacent to the right side of the host vehicle lane 101. Furthermore, reference numerals 102L and 102R indicate the left and right dividing lines of the host vehicle lane 101, respectively. Reference numeral 103 indicates the right dividing line of the right lane 101R. Reference numeral 104 indicates the left dividing line of the left lane 101L.

[0071] 2, reference numeral 110 denotes the imaging range (angle of view) of the stereo camera 11. Reference numerals 111L and 111R denote the scanning ranges of the left front side sensor 37lf and the right front side sensor 37rf of the on-vehicle radar device 37.

[0072] 2, reference numeral 105 (two-dot chain line) indicates an imaginary line passing through approximately the center between the left and right dividing lines 102L, 102R of the host vehicle's lane 101. When the host vehicle M travels along the host vehicle's lane 101 under normal lane centering control (ALKC), the host vehicle M is controlled to travel based on the imaginary center line 105.

[0073] In this case, as shown in FIG. 2, it is assumed that multiple leading vehicles are traveling ahead of the host vehicle M. Here, reference symbol M1 is the leading vehicle traveling immediately in front of the host vehicle M (hereinafter referred to as the first leading vehicle). Reference symbol M2 is the leading vehicle traveling immediately in front of the first leading vehicle M1 (hereinafter referred to as the second leading vehicle). This second leading vehicle M2 is the second leading vehicle ahead of the host vehicle M. Reference symbol M3 is the leading vehicle traveling immediately in front of the second leading vehicle M2 (hereinafter referred to as the third leading vehicle). This third leading vehicle M3 is the third leading vehicle ahead of the host vehicle M.

[0074] 2, reference numeral 200 denotes an obstacle such as a three-dimensional fallen object (hereinafter referred to as an obstacle, etc.). This obstacle, etc. 200 is assumed to be an object that is located ahead of the host vehicle M on a travel route set within the host vehicle travel lane 101 of the host vehicle M and that may obstruct the travel of the host vehicle M.

[0075] In the situation shown in FIG. 2, the obstacle 200 is assumed to be located in a position that cannot be directly recognized by the surrounding environment recognition device (camera 11, radar 37) of the driving assistance device 1 of the host vehicle M.

[0076] Here, the following situations can be considered as positions that cannot be directly recognized by the surrounding environment recognition device of the driving assistance device 1 of the host vehicle M. For example, consider a case where multiple preceding vehicles (M1, M2, M3) are traveling ahead of the host vehicle M. Note that although the example in FIG. 2 illustrates only three preceding vehicles, it is also possible to consider a situation where there are further preceding vehicles ahead.

[0077] Here, for example, when the subject vehicle M and multiple preceding vehicles (M1, M2, M3) are normally traveling on the same lane and in a normal environment where there are no obstacles or the like on the traveling lane, all of these vehicles are traveling approximately in a line along the center virtual line 105 while maintaining a predetermined inter-vehicle distance.

[0078] Consider a situation in which, under such normal circumstances, an obstacle 200 is present in front of a preceding vehicle several vehicles ahead as viewed from the host vehicle M. In this case, the forward field of view of the host vehicle M is blocked by the multiple preceding vehicles. Therefore, it is considered that the driving assistance device 1 of the host vehicle M is in a situation in which the obstacle 200 cannot be directly seen.

[0079] At this time, the leading vehicle among the plurality of leading vehicles (M1, M2, M3) will eventually recognize the obstacle 200. As a result, the leading vehicle will take a route that deviates from the normal route along the center virtual line 105 to avoid the obstacle 200.

[0080] Therefore, in the driving assistance device 1 of this embodiment, when the vehicle M is traveling on a road in driving assistance mode, the presence or absence, position, size, etc. of an obstacle 200 ahead is estimated by recognizing the distribution of behaviors of multiple preceding vehicles (M1, M2, M3) before directly recognizing the obstacle 200.

[0081] If it is estimated that an obstacle 200 is present, a travel route that can avoid the estimated area where the obstacle 200 exists is calculated, and obstacle avoidance control is initiated along an appropriate travel route. As a result, the driving assistance device 1 of this embodiment performs travel control along a travel route that can avoid the obstacle 200 before the obstacle 200 can be directly recognized. Therefore, the host vehicle M can perform safe and reliable obstacle avoidance control.

[0082] To achieve this, first, the driving assistance device 1 of this embodiment mounted on the host vehicle M determines whether the behavior of the multiple preceding vehicles is a behavior that avoids the obstacle 200. Such a determination is made as follows. For example, the situation shown in FIG. 2 illustrates a situation in which the host vehicle M is traveling in the illustrated position (center lane 101 of a three-lane road) and there are multiple preceding vehicles (M1, M2, M3) traveling ahead, and an obstacle 200 is also present. At this time, the obstacle 200 is blocked by the multiple preceding vehicles (M1, M2, M3), and the host vehicle M cannot directly recognize the obstacle 200.

[0083] At this time, both the first leading vehicle M1 and the second leading vehicle M2 have their right turn indicators WR flashing and are traveling on routes that deviate from the virtual center line 105 of the host vehicle's lane 101. This can be recognized by a surrounding environment recognition device (e.g., stereo camera 11) in the driving assistance device 1 of the host vehicle M. In this case, the driving assistance device 1 of the host vehicle M can easily recognize the first leading vehicle M1 because there is nothing obstructing the view between the host vehicle M and the first leading vehicle M1.

[0084] 2 indicates the amount of change in lateral position (amount of route deviation) when the second preceding vehicle M2 deviates laterally to the right from the central imaginary line 105.

[0085] In a normal situation (while traveling along the central imaginary line 105), the second preceding vehicle M2 should be in a position where it is blocked by the first preceding vehicle M1. However, in the situation shown in Fig. 2, the route deviation amount W1 of the second preceding vehicle M2 from the central imaginary line 105 is large, so it is considered that a part of the second preceding vehicle M2 can be recognized by the driving assistance device 1 of the host vehicle M through the first preceding vehicle M1.

[0086] Furthermore, when the second leading vehicle M2 is viewed from the host vehicle M, the first leading vehicle M1 is seen between them. In this case, it may be possible to recognize part of the second leading vehicle M2 from the host vehicle M through the rear window and front window of the first leading vehicle M1. Furthermore, the shadow of the second leading vehicle M2 may be projected onto the road surface, and this shadow may be visible from the host vehicle M. For these reasons, at least part of the second leading vehicle M2 is visible from the host vehicle M, making it possible to recognize its presence.

[0087] Then, the lateral position change amount (route deviation amount W1) of each preceding vehicle (M1, M2, etc.) can be estimated from the relative positional relationship between the host vehicle M and each preceding vehicle (M1, M2, etc.). Therefore, the behavior distribution (lateral position distribution) of each vehicle can be calculated. Such a technology for recognizing multiple preceding vehicles can be a well-known technology used in conventional driving assistance devices.

[0088] Furthermore, the driving assistance device 1 of the host vehicle M may also be able to recognize a third preceding vehicle M3. In this case, the third preceding vehicle M3 shown in Fig. 2 is flashing its left turn signal WL and is in the process of returning to the host vehicle's lane 101 from a driving route that had deviated from the virtual center line 105 of the host vehicle's lane 101. At this time, the driving assistance device 1 of the host vehicle M may be able to recognize a portion of the left side of the third preceding vehicle M3.

[0089] Therefore, for example, if it is recognized that at least two of the multiple preceding vehicles (M1, M2, M3) (e.g., M1 and M2) are both flashing their turn signals and deviating from the driving lane by a predetermined amount, it can be estimated that these two preceding vehicles (M1 and M2) are behaving in a way to avoid an obstacle 200 ahead.

[0090] In other words, for example, it is not possible to determine from the behavior of only one preceding vehicle whether the behavior is to avoid the obstacle 200 or whether the vehicle is simply meandering. However, if multiple vehicles (two or more) exhibit similar behavior, it can be estimated that the behavior is likely to be to avoid the obstacle 200. Therefore, by recognizing the behavior of multiple preceding vehicles, it is possible to more accurately estimate the presence of the obstacle 200.

[0091] At this time, the driving assistance device 1 of the host vehicle M estimates an estimated area 200x where an obstacle, etc. 200 is likely to exist from the behavior distribution of at least two of the multiple preceding vehicles (M1, M2, M3).

[0092] The situation shown in Fig. 2 will now be described in more detail. Reference numeral 105b in Fig. 2 indicates the deviation route (avoidance route; dotted line) of the second preceding vehicle M2. Reference numeral B indicates the timing at which the second preceding vehicle M2 takes the deviation route 105b. Reference numeral 105c in Fig. 2 indicates the deviation route (avoidance route; long-dotted line) of the first preceding vehicle M1. Reference numeral C indicates the timing at which the first preceding vehicle M1 takes the deviation route 105c.

[0093] In this case, when the first leading vehicle M1 is in the position shown in Fig. 2, it is considered that it is in a situation where it can directly recognize the obstacle 200 by itself. However, in an earlier situation (not shown), it is considered that the first leading vehicle M1 is unable to directly recognize the obstacle 200 because it is blocked by the second leading vehicle M2. For this reason, it is only after the second leading vehicle M2 takes the deviation travel route 105b that the first leading vehicle M1 is in a situation where it can recognize the obstacle 200. At this time, the first leading vehicle M1 recognizes the behavior of the second leading vehicle M2 traveling immediately ahead, or directly recognizes the obstacle 200, by conventional obstacle avoidance control, and control is performed to avoid the obstacle 200 based on the recognition results.

[0094] This means that the first preceding vehicle M1 will take the deviation travel route 105c, which starts at point C, which is later than the start timing (point B) of the deviation travel route 105b of the second preceding vehicle M2. In this case, the control start timing of the first preceding vehicle M1 will be later than that of the second preceding vehicle M2, and therefore the first preceding vehicle M1 will tend to respond by making a sudden steering maneuver.

[0095] If we apply this situation to the host vehicle M and the first preceding vehicle M1, the following will occur. That is, if the host vehicle M recognizes the behavior of the first preceding vehicle M1 and then takes a predetermined deviation travel route, the host vehicle M will start obstacle avoidance control at a later timing than the first preceding vehicle M1. Also, if the host vehicle M directly recognizes an obstacle 200 and then takes a predetermined deviation travel route, the host vehicle M will start obstacle avoidance control at an even later timing than the first preceding vehicle M1. Therefore, in this case, the host vehicle M may be forced to make sudden steering or braking without any room to maneuver. The driving assistance device 1 of this embodiment is a device for avoiding such sudden behavior without any room to maneuver in the host vehicle M.

[0096] Furthermore, Fig. 3 illustrates another situation regarding the determination of whether the behavior of multiple preceding vehicles is a behavior to avoid an obstacle 200 or not. The situation shown in Fig. 3 is basically similar to the situation shown in Fig. 2. However, in the situation shown in Fig. 3, the driving assistance device 1 of the host vehicle M recognizes the surrounding environment as follows.

[0097] That is, the driving assistance device 1 of the host vehicle M recognizes that the second preceding vehicle M2 is flashing its right turn signal WR and is traveling along a driving route 105b (dotted line) that deviates from the virtual center line 105 of the host vehicle's driving lane 101. Furthermore, at this time, the driving assistance device 1 of the host vehicle M recognizes that the first preceding vehicle M1 has its brake lights on. Here, the symbol ST in Fig. 3 indicates a state in which the brake lights of the first preceding vehicle M1 are on.

[0098] Even when such a situation is recognized, the driving assistance device 1 of this embodiment estimates that the behavior of the two preceding vehicles (M1, M2) is a behavior that avoids the obstacle 200. Then, when it is recognized that the brake lights ST of some of the preceding vehicles (particularly the preceding vehicle immediately before the host vehicle M) are illuminated, as in the example situation in Fig. 3, it can be estimated that there is an even higher possibility that the preceding vehicle (first preceding vehicle M1 in Fig. 3) is adopting a behavior that avoids the obstacle 200.

[0099] Therefore, as described above, if it is possible to recognize the state of the turn signals (see FIG. 2) and the state of the brake lights (see FIG. 3) of the multiple preceding vehicles in addition to estimating the distribution of the lateral position changes (route deviation amount W1) of the multiple preceding vehicles, it is possible to more accurately estimate that the behavior of each of the multiple preceding vehicles is a behavior that avoids an obstacle, etc.

[0100] Furthermore, even in the situation of Fig. 3, the driving assistance device 1 of the host vehicle M may be able to recognize the third preceding vehicle M3. In this case, as in the situation of Fig. 2, the driving assistance device 1 of the host vehicle M may estimate that the behavior of the third preceding vehicle M3 is a behavior that avoids the obstacle 200.

[0101] The driving assistance device 1 of this embodiment recognizes the behaviors of multiple preceding vehicles and determines whether the behaviors of the multiple preceding vehicles are behaviors for avoiding an obstacle or the like. For this reason, in the examples of FIGS. 2 and 3, three preceding vehicles (M1, M2, M3) are shown as the multiple preceding vehicles. However, this is not limited to this example. If the driving assistance device 1 of this embodiment can recognize the behaviors of at least two preceding vehicles (M1, M2), it can determine (estimate) whether the behaviors of these (at least two preceding vehicles) are behaviors for avoiding an obstacle or the like 200 based on the behaviors (of the at least two preceding vehicles).

[0102] 2 and 3 show an example in which the second preceding vehicle M2 is traveling while straddling the right lane marking 102R. Also, an example in which the third preceding vehicle M3 is attempting to return to the same lane as the host vehicle M is shown. However, the behavior of the multiple preceding vehicles is not limited to these examples. For example, a departure can also be determined when the second preceding vehicle M2 or the third preceding vehicle deviates from the same host vehicle lane 101 as the host vehicle M and then changes lanes to the right lane 101R or left lane 101L adjacent to the same lane.

[0103] 2 and 3, all of the multiple preceding vehicles (M1, M2, M3) deviate into the right lane 101R. However, the present invention is not limited to the illustrated example. For example, as shown in FIGS. 2 and 3, if the road 100 on which the host vehicle M and the multiple preceding vehicles (M1, M2, M3) are traveling is a three-lane road, and all of the vehicles are traveling in the center lane 101, then even if any of the multiple preceding vehicles deviates into the left lane 101L (or even changes lanes to the left lane 101L), it can still be determined that a departure has occurred.

[0104] 2 and 3, the road 100 on which the host vehicle M and the multiple preceding vehicles (M1, M2, M3) are traveling is illustrated as a road with three lanes on each side, but this is not limited to this. For example, the two lanes (101L, 101) on the left side shown in Figures 2 and 3 may be considered as the road on which the host vehicle M and the multiple preceding vehicles (M1, M2, M3) are traveling, and the right lane 101R in Figures 2 and 3 may be considered as the oncoming lane.

[0105] Next, the flow of operation of the driving assistance device 1 of this embodiment will be explained below using the flowchart in Fig. 4. In the following explanation, only the operation related to obstacle avoidance control in the driving assistance device 1 of this embodiment will be particularly shown, and explanations of ordinary general processes and operations that are executed simultaneously in parallel in a normal driving assistance device 1 will be omitted.

[0106] First, it is assumed that the host vehicle M equipped with the driving assistance device 1 of this embodiment is traveling on a road as shown in Fig. 2. At this time, it is assumed that the driving assistance device 1 of the host vehicle M is set to a first driving control mode (driving assistance mode) or a second driving control mode (automated driving mode). In other words, it is assumed that the driving assistance device 1 of the host vehicle M controls the driving of the host vehicle M while executing predetermined automatic driving assistance functions such as adaptive cruise control (ACC), lane centering control (ALKC), and lane departure prevention control (ALKB). In this case, the driving assistance device 1 may also execute a hands-off function (second driving control mode).

[0107] In this situation, the driving assistance device 1 of the vehicle M operates the surrounding environment recognition device (the camera 11 and the on-board radar device 37) in step S11 of Fig. 4 to acquire information about the surrounding environment of the vehicle M. The driving assistance device 1 also performs predetermined processing on the acquired surrounding environment information. As a result, the driving assistance device 1 continues to recognize the status of the surrounding environment (presence or absence of a preceding vehicle, an obstacle on the road, etc.).

[0108] In the process of step S11, the driving assistance device 1 checks whether or not the presence of an obstacle or the like has been recognized ahead. If an obstacle or the like has been recognized, the process proceeds to step S21. If an obstacle or the like has not been recognized, the process proceeds to the next step S12.

[0109] When an obstacle or the like is recognized and the process proceeds to step S21, this is the case when the driving assistance device 1 of the vehicle M directly recognizes an obstacle or the like present in front of the vehicle M. In this case, a conventional obstacle avoidance control is executed based on the recognized obstacle or the like. After that, when the series of processes is completed, the process returns to the original processing step (return).

[0110] Meanwhile, in step S12, the driving assistance device 1 checks whether or not a preceding vehicle has been recognized based on the surrounding environment information acquired by the surrounding environment recognition device (camera 11 or on-board radar device 37). If a preceding vehicle has not been recognized, the process returns to step S11. If a preceding vehicle has been recognized, the process proceeds to the next step S13.

[0111] Next, in step S13, the driving assistance device 1 checks whether only one or more preceding vehicles have been recognized in the processing of the above-mentioned step S12. If only one preceding vehicle has been recognized, the processing proceeds to step S22. If multiple preceding vehicles have been recognized, the processing proceeds to the next step S14.

[0112] If only one preceding vehicle is recognized, the process proceeds to step S22, in which the driving assistance device 1 executes normal obstacle avoidance control based on the behavior of the recognized preceding vehicle. After that, when the series of processes is completed, the process returns to the original processing step (RETURN).

[0113] Meanwhile, in step S14, the driving assistance device 1 calculates the distribution of the behaviors of the recognized plurality of preceding vehicles and estimates whether or not there is an obstacle or the like ahead that the host vehicle has not been able to recognize. In this case, the driving control unit (driving_ECU) 14 of the driving assistance device 1 functions as an obstacle estimation unit that estimates the presence of an obstacle or the like ahead based on the behavior distribution of the plurality of preceding vehicles recognized by the surrounding environment recognition device (camera 11 and on-board radar device 37).

[0114] Here, to estimate the presence or absence of an obstacle, etc., based on the behavior of multiple preceding vehicles, as explained with reference to FIGS. 2 and 3, first, the relative positions of the host vehicle and the recognized multiple preceding vehicles are obtained, and the lateral position change amount (route deviation amount) of each preceding vehicle is estimated. This calculates the lateral position distribution of the preceding vehicles. If the lateral position change amount (route deviation amount) of the multiple preceding vehicles is equal to or greater than a predetermined threshold, each preceding vehicle is estimated to be behaving in a manner to avoid an obstacle, etc. As mentioned above, in this case, the behaviors of the multiple preceding vehicles do not necessarily have to be identical. If it is thus estimated that the multiple preceding vehicles are behaving in a manner to avoid an obstacle, etc., the process proceeds to the next step S15. In the process of step S14, the predetermined threshold may be changed as appropriate if the blinking of the turn signal or the illumination of the brake lights is recognized.

[0115] Furthermore, if the behavior distribution of the multiple preceding vehicles is within the threshold in the process of step S14, it can be assumed that there are no obstacles ahead. In this case, the process of step S14 is repeated while continuing normal adaptive cruise control (ACC), lane centering control (ALKC), etc.

[0116] Next, in step S15, the driving support device 1 estimates the position (relative position with respect to the vehicle or position on the road) and size (area where the obstacle, etc. is present) of the estimated obstacle, etc. based on the behaviors of the multiple preceding vehicles, and estimates the area where the obstacle, etc. is present. In this case, the driving control unit (driving_ECU) 14 of the driving support device 1 functions as an obstacle estimation unit that estimates the position, size, etc. (area where the obstacle, etc. is present) of the obstacle, etc. when the presence of the obstacle, etc. is estimated.

[0117] If the behavior of multiple preceding vehicles is estimated to be an avoidance behavior of an obstacle, etc. in the process of step S14 described above, it can be estimated that an obstacle, etc. is present near each preceding vehicle. Therefore, by calculating the position of the host vehicle and the positions of the preceding vehicles, the relative positions of the host vehicle and the obstacle, etc. can be estimated.

[0118] The size of obstacles, etc. can also be estimated from various numerical data such as the width of the lane in which the vehicle is traveling, the widths of the vehicle itself and the preceding vehicle, and the amount of lateral position change (route deviation) of multiple preceding vehicles. For example, the larger the amount of lateral position change (route deviation) of multiple preceding vehicles, the larger the estimated size of the obstacle, etc. The width of the lane in which the vehicle is traveling can be calculated by recognizing left and right lane markings. The vehicle width of the vehicle itself can be calculated by referring to information previously stored as vehicle information by the driving assistance device 1 of the vehicle. The vehicle width of the preceding vehicle can be calculated based on image information from the stereo camera 11, or by referring to a predetermined fixed value (for example, the average vehicle width of a passenger car) as an estimated value. The area in which the obstacle, etc. exists can then be estimated from this estimated information.

[0119] Next, in step S16, the driving assistance device 1 calculates a plurality of candidate routes for the host vehicle to avoid the area where the estimated obstacles, etc. are present. In this case, the driving control unit (driving_ECU) 14 of the driving assistance device 1 functions as a route calculation unit. Note that the number of candidate routes calculated here does not necessarily need to be multiple, and a single route that is considered to be the most appropriate may be presented.

[0120] Once the position and area of ​​the obstacle, etc. are estimated in the process of step S15 described above, the distance from the host vehicle to the obstacle, etc. and the arrival time can be estimated from the relative position between the obstacle, etc. and the host vehicle and the vehicle speed. This makes it possible to set the timing for the host vehicle to start obstacle avoidance control.

[0121] Further, the candidate travel paths for the host vehicle to avoid obstacles are calculated based on the trajectories of multiple preceding vehicles, the estimated vehicle widths of each preceding vehicle (which may be fixed values ​​as described above), the vehicle width of the host vehicle, a predetermined safety margin, etc. In this case, the candidate travel paths are calculated as a travel path area having a predetermined area in the lateral direction with the expected travel path as the center.

[0122] Here, Fig. 5 conceptually shows a plurality of candidate travel paths calculated in the processing of step S16 in Fig. 4. In Fig. 5, reference numeral 120 (solid line) indicates a travel path area when the host vehicle M is traveling along the host vehicle travel lane 101. This travel path area 120 is a travel path area during normal lane centering control (ALKC) before the start of obstacle avoidance control.

[0123] Reference numeral 121 (solid line) denotes a first candidate path area among the multiple candidate paths calculated in the processing of step S16 in Fig. 4. This first candidate path area 121 is calculated as a candidate path area in which obstacle avoidance control can be performed before the host vehicle M directly recognizes the obstacle 200, based on the estimated area 200x of the obstacle 200 inferred by recognizing the behavior distribution of the first leading vehicle M1 and the second leading vehicle M2 in Fig. 2. In other words, it is calculated as a candidate path area in which the start timing of the obstacle avoidance control is set earlier than that of the first leading vehicle M1, the second leading vehicle M2, etc. in Fig. 2. Note that reference numeral A denotes a control start point in which obstacle avoidance control is performed on a deviation travel route that passes through this first candidate path area 121.

[0124] Reference numeral 122 (broken line) indicates a second candidate path area among the multiple candidate paths calculated in the processing of step S16 in Fig. 4. This second candidate path area 122 is a path area that roughly corresponds to the trajectory of the second preceding vehicle M2 in Fig. 2 (see deviation travel route 105b in Fig. 2). Note that the point at which obstacle avoidance control for the second preceding vehicle M2 is started is indicated by reference numeral B.

[0125] Reference numeral 123 (dash-dotted line) indicates a third candidate path area among the multiple candidate paths calculated in the processing of step S16 in Fig. 4. This third candidate path area 123 is a path area that roughly corresponds to the trajectory of the first preceding vehicle M1 in Fig. 2 (see deviation travel route 105c in Fig. 2). Note that the point at which obstacle avoidance control for the first preceding vehicle M1 is started is indicated by reference numeral C.

[0126] Reference numeral 124 (chain double-dashed line) indicates a fourth candidate path area among the multiple candidate paths calculated in the processing of step S16 in Fig. 4. This fourth candidate path area 124 is a path area that roughly corresponds to the driving route when the vehicle deviates into the left lane 101L. Note that the control start point when obstacle avoidance control is performed on a deviation driving route that passes through this fourth candidate path area 124 is equivalent to point A.

[0127] These multiple candidate path areas (121, 122, 123, 124) are all continuous path areas branching off from the path area 120. Furthermore, each of the candidate path areas (121, 122, 123, 124) is calculated as a path area that reliably avoids the estimated area 200x of the obstacle 200, etc.

[0128] Next, in step S17, the driving support device 1 selects an appropriate route area from the multiple route candidates calculated in the process of step S16. In this case, the driving control unit (driving_ECU) 14 of the driving support device 1 functions as a route selection unit. Here, the appropriate route selected is basically a route that deviates to the right.

[0129] In the example shown in Fig. 5, the recognized obstacle 200 is estimated to be located to the left within the vehicle's driving lane 101. Under these circumstances, it is clear that when the vehicle M avoids the obstacle 200, taking a route that deviates to the right will result in a smaller change in lateral position than taking a route that deviates to the left. Therefore, in the example shown in Fig. 5, one of the candidate routes (121, 122, 123) to the right is preferentially selected.

[0130] As described above, the distance between the vehicle M and the obstacle 200 and the arrival time to the obstacle 200 are estimated from the relative positions of the vehicle M and the obstacle 200 and the vehicle speed of the vehicle M. Then, the control start timing is set based on information such as the estimated distance or arrival time. For example, for three candidate routes (121, 122, 123) to the right, the earliest control start timing is the first candidate route area 121 (point A), the second candidate route area 122 (point B), and the third candidate route area 123 (point C).

[0131] That is, as shown in FIG. 5, when the first candidate path area 121 is selected, the control start timing can be set to point A, which is the earliest. When the second candidate path area 122 is selected, the control start timing becomes point B, which is later than point A by symbol D1 in FIG. 5. When the third candidate path area 123 is selected, the control start timing becomes point C, which is later than point A by symbol D in FIG. 5 and later than point B by symbol D2 in FIG. 5. Therefore, a path with an appropriate control start timing is selected taking into consideration the estimated distance or arrival time. In this case, the longer the distance or arrival time to the obstacle 200, the earlier the control start timing can be set with ample time, thereby enabling avoidance with gradual lateral movement.

[0132] Once the route has been selected in this manner, in the next step S18, travel control (obstacle avoidance control) is started to cause the host vehicle to travel along the route selected in the processing of step S17. The obstacle avoidance control performed here includes, for example, automatic steering control, automatic braking control, etc.

[0133] Here, when obstacle avoidance control is initiated, the driving assistance device 1 first checks the surrounding conditions using the surrounding environment recognition device (stereo camera 11, on-board radar device 37). For example, if there are other vehicles traveling around the host vehicle M, particularly behind or to the side, and the host vehicle were to take a driving route that deviates in the direction of the other vehicles, there is a possibility that the host vehicle would obstruct the driving of the other vehicles. Therefore, when the host vehicle initiates obstacle avoidance control and takes a predetermined deviation driving route, the driving assistance device 1 first checks the safety of the surroundings.

[0134] The example shown in Fig. 6 illustrates a situation in which, for example, a first candidate path area 121 is selected and other vehicles are present around the host vehicle M. More specifically, in Fig. 6, similar to the situation shown in Fig. 2, the host vehicle M is traveling in the host vehicle driving lane 101, and the first leading vehicle M1 and the second leading vehicle M2 are traveling to avoid an obstacle 200. At this time, the host vehicle M estimates the presence of the obstacle 200 based on the behavior of the first leading vehicle M1 and the second leading vehicle M2, and selects and sets the first candidate path area 121 (see the area 121 indicated by the dotted line in Fig. 6) calculated thereby. Under such a situation, the driving assistance device 1 of the host vehicle M is about to execute driving control using obstacle avoidance control.

[0135] Here, the driving assistance device 1 of the host vehicle M first recognizes another vehicle (hereinafter referred to as a nearby other vehicle; see symbol M4 in Figure 6) traveling behind or to the side of the host vehicle M in the right lane 101R adjacent to the host vehicle's driving lane 101.

[0136] In this case, the nearby other vehicle M4 may further decelerate upon recognizing the first leading vehicle M1, the second leading vehicle M2, etc. that are traveling on the deviation route (see brake lights ST).

[0137] Therefore, under such circumstances, if the host vehicle M attempts to perform travel control along the already selected first travel path candidate area 121, there is a possibility that the travel of the nearby other vehicle M4 will be obstructed.

[0138] Therefore, in such a situation, the driving assistance device 1 of the host vehicle M adjusts the position of the selected first candidate route area 121. In this case, the driving control unit (driving_ECU) 14 of the driving assistance device 1 functions as a route adjustment unit that adjusts the position of the selected route area according to the surrounding environment of the host vehicle M.

[0139] For example, in the example shown in FIG. 6, the driving assistance device 1 of the host vehicle M determines whether the selected first route candidate area 121 is in the direction indicated by the arrow S in FIG. 6 (lateral direction) or the direction indicated by the arrow S in FIG. Obstacles The lateral position of the host vehicle M is adjusted by a predetermined amount to the right (toward the obstacle 200) to set a new candidate route area 121x (solid line). This new candidate route area 121x is a route area in which the amount of change in lateral position to the right is suppressed while taking into account the estimated area 200x of the obstacle 200. This enables the host vehicle M to avoid the obstacle 200 while also preventing interference with the nearby other vehicle M4.

[0140] 6, the nearby vehicle M4 is exemplified as a vehicle traveling behind or to the side in an adjacent lane, but is not limited to this example. For example, if the right lane 101R shown in FIG. 6 is considered to be an oncoming lane, the same can be considered when there is an oncoming vehicle approaching from the front in the oncoming lane.

[0141] In this way, in the driving assistance device 1 of this embodiment, after selecting a candidate route area, if other vehicles in the vicinity (following vehicles in adjacent lanes, vehicles traveling alongside, oncoming vehicles, etc.) are recognized, a position adjustment process is performed on the selected candidate route area to ensure safer driving of the vehicle M.

[0142] In this way, in the processing of step S18, the driving assistance device 1 performs obstacle avoidance control to avoid the obstacle 200. During this process, the driving assistance device 1 of the host vehicle M becomes able to directly recognize the estimated obstacle 200. In other words, when the host vehicle M approaches the position of the obstacle 200, the obstacle 200 that was blocked by the first preceding vehicle M1 becomes able to be directly recognized by the driving assistance device 1 of the host vehicle M. When this situation occurs, the driving assistance device 1 performs normal driving control corresponding to the directly recognized obstacle 200.

[0143] After avoiding the obstacle 200 in this way, the host vehicle M is returned to the original host vehicle lane 101. Then, normal driving control such as adaptive cruise control (ACC), lane centering control (ALKC), etc. along the original host vehicle lane 101 is continued (return).

[0144] As described above, according to the first embodiment, the behaviors of a plurality of preceding vehicles are recognized, so that it is possible to accurately determine whether the behavior of the preceding vehicle is a behavior to avoid an obstacle or the like, or whether the preceding vehicle is simply meandering.

[0145] Furthermore, if the behavior of multiple preceding vehicles is determined to be behavior that avoids obstacles, etc., it is possible to estimate the presence of obstacles, etc. ahead based on the behavior distribution of the multiple preceding vehicles, even in a situation where the surrounding environment recognition device cannot directly recognize obstacles, etc.

[0146] Furthermore, if it is estimated that an obstacle or the like is present ahead, the position, size, etc. of the obstacle or the like (the area in which the obstacle or the like exists) can be estimated based on the behavior distribution of multiple preceding vehicles.

[0147] When the presence of an obstacle or the like ahead is estimated and the area in which the obstacle or the like is present can be estimated, multiple travel path areas for avoiding the estimated obstacle or the like can be calculated. In this case, an appropriate travel path for obstacle avoidance control can be selected according to the relative position between the host vehicle and the estimated obstacle or the like. This makes it possible to start obstacle avoidance control early and reliably, with ample time to get ahead of multiple preceding vehicles.

[0148] Furthermore, when multiple preceding vehicles are traveling and performing actions to avoid obstacles, etc., even if these multiple preceding vehicles are avoiding the obstacles, etc. by, for example, sudden steering or sudden braking, the subject vehicle can recognize the behavior of the multiple preceding vehicles and begin to take action to avoid the obstacles, etc., earlier than the multiple preceding vehicles and with ample time to spare.

[0149] In the above-described embodiment, as shown in Fig. 5, the recognized obstacle 200 is estimated to be located to the left within the range of the host vehicle's driving lane 101. Therefore, the control process is exemplified in which one of the candidate paths (121, 122, 123) to the right is preferentially selected (step S17 in Fig. 4).

[0150] In the above-described embodiment, the vehicle M checks the surrounding conditions after selecting the right-side candidate path (step S17 in FIG. 4). In this case, when it is recognized that there is a surrounding vehicle (see symbol M4 in FIG. 6) such as a following vehicle or a vehicle traveling alongside in the adjacent lane on the right, the control process adjusts the lateral position of the selected right-side candidate path in consideration of the presence of the surrounding vehicle M4 (step S18 in FIG. 4).

[0151] However, in such a situation, if there is another candidate path that does not require lateral position adjustment, a control process may be performed to select that candidate path (the candidate that does not require lateral position adjustment) even if the amount of lateral position change is greater.

[0152] Therefore, the following control processing can be considered for the processing of step S17 in Fig. 4 (candidate route selection processing): Fig. 7 is a flowchart showing a subroutine of a modified example of the candidate route selection processing (step S17 in Fig. 4) in the embodiment described above.

[0153] In this modification, the driving assistance device 1 first performs processing to check the surrounding conditions using the surrounding environment recognition device (stereo camera 11, on-board radar device 37) in the processing of step S31 in FIG.

[0154] Next, in step S32, the driving assistance device 1 checks whether there is a candidate route to the right among the multiple candidate routes calculated in the process of step S16 (see FIG. 4). If there is a candidate route to the right, the process proceeds to the next step S33. If there is no candidate route to the right, the process proceeds to step S35.

[0155] In step S33, the driving assistance device 1 checks whether or not there is a nearby vehicle in the adjacent lane to the right of the host vehicle M, based on the processing result of step S31 described above. If it is confirmed that there is a nearby vehicle on the right, the process proceeds to step S34. If it is not confirmed that there is a nearby vehicle on the right, the process proceeds to step S38.

[0156] In step S34, the driving assistance device 1 checks whether there is a candidate route to the left among the multiple candidate routes calculated in the process of step S16 (see FIG. 4). If there is a candidate route to the left, the process proceeds to the next step S35. If there is no candidate route to the left, the process proceeds to step S37.

[0157] In step S35, the driving assistance device 1 checks whether or not a nearby vehicle is present in the adjacent lane to the left of the host vehicle M, based on the processing result of step S31 described above. If it is confirmed that a nearby vehicle is present on the left, the process proceeds to step S36. If it is not confirmed that a nearby vehicle is present on the left, the process proceeds to step S39.

[0158] In step S36, the driving assistance device 1 checks whether there is a candidate route to the right among the multiple candidate routes calculated in the process of step S16 described above (see FIG. 4). Note that a similar check is performed in the process of step S32 described above, but the process flow is such that, in both cases where there is a candidate route to the right in the process of step S32 described above and where there is no candidate route to the right, the process of step S36 is performed, and therefore a second check is performed. Here, if there is a candidate route to the right, the process proceeds to the next step S37. On the other hand, if there is no candidate route to the right, the process proceeds to the process of step S40.

[0159] In step S37, the driving assistance device 1 selects a candidate path to the right and performs an adjustment process for the selected candidate path. This adjustment process is the same as the process in step S18 of Fig. 6 and Fig. 4 described in the above embodiment. Thereafter, the series of processes ends and the process returns to the original process (return).

[0160] In step S38, the driving assistance device 1 selects a route candidate to the right. After that, the series of processes ends and the process returns to the original process (RETURN). The process in this case is the same as the process of step S17 in FIG. 4 described in the above embodiment, in which the route candidate to the right is preferentially selected.

[0161] In step S39, the driving assistance device 1 selects a candidate route to the left, and then ends the series of processes and returns to the original process (return).

[0162] In step S40, the driving assistance device 1 selects a candidate path to the left and performs an adjustment process for the selected candidate path. This adjustment process is substantially the same as the process in step S37 described above (the process in step S18 in FIG. 6 and FIG. 4 described in the above embodiment). In this case, the right side in the above process can be replaced with the left side. Thereafter, the series of processes is terminated and the original process is returned to.

[0163] The control process of this modification can also achieve substantially the same effects as the above-described embodiment. Furthermore, in this modification, when selecting a route candidate, the status of other vehicles in the vicinity is first confirmed, and the selection is made based on the recognized status of other vehicles in the vicinity, thereby enabling safer and easier control selection.

[0164] In the driving assistance device 1 of this embodiment, the stereo camera 11 included in the camera unit 10 is exemplified as a surrounding environment recognition device that acquires image data representing the surrounding environment while the host vehicle is traveling, but the present invention is not limited to this example. For example, a monocular camera can be used as the surrounding environment recognition device instead of the stereo camera 11. Furthermore, although the in-vehicle radar device 37 is exemplified as a surrounding environment recognition device that recognizes the surrounding environment around the vehicle, the present invention is not limited to this example. For example, a LiDAR (Light Detection and Ranging) device can be used as the surrounding environment recognition device instead of the in-vehicle radar device 37.

[0165] The present invention is not limited to the above-described embodiments, and various modifications and applications can be made without departing from the spirit and scope of the invention. Furthermore, the above-described embodiments include inventions at various stages, and various inventions can be extracted by appropriately combining the disclosed multiple constituent elements. For example, if the problem to be solved by the invention can be solved and the effects of the invention can be obtained even if some constituent elements are deleted from all the constituent elements shown in one embodiment, the configuration from which these constituent elements are deleted can be extracted as the invention. Furthermore, constituent elements from different embodiments may be appropriately combined. The present invention is not limited by specific embodiments other than as limited by the appended claims. [Explanation of symbols]

[0166] 1...Driving assistance device 10...Camera unit 11...Stereo camera (surrounding environment recognition device) 12...Image Processing Unit (IPU) 13...Image recognition unit (Image recognition ECU) 14...Travel control unit (Travel_ECU) 21...Cockpit control unit (CP_ECU) 22...Engine control unit (E / G_ECU) 23...Transmission control unit (T / M_ECU) 24...Brake control unit (BK_ECU) 25...Power steering control unit (PS_ECU) 31...Human Machine Interface (HMI) 32...Throttle actuator 33...Hydraulic control circuit 34...Brake actuator 35...Electric power steering motor 36...Locator unit 36a...GNSS sensor 36b…High-precision road map database (road map DB) 37...In-vehicle radar device (surrounding environment recognition device) 37lf...Front left side sensor 37rf...Right front side sensor 37lr...Left rear side sensor 37rr...Right rear side sensor 38...Rear sensor 100...Travel route 101...Drive lane (center lane) 101L...Left lane 101R…Right lane 102L: Left lane dividing line of center lane 102R: Right-hand dividing line of center lane 103...Right lane marking 104...Left lane dividing line 105...Central virtual line 105b...Deviated driving route of the second preceding vehicle 105c…Deviated driving route of the first leading vehicle 110...Stereo camera imaging range (angle of view) 111L: Scanning range of the left front side sensor 111R: Scanning range of right front side sensor 120...Route area 121...First route candidate area 121x…First route candidate area (after adjustment) 122...Second route candidate area 123...Third route candidate area 124...Fourth route candidate area 200...Obstacles, etc. 200x: Estimated area of ​​obstacles, etc. M...own vehicle M4: Other vehicles in the vicinity ST…Brake light W1: Route deviation amount WL…Left direction indicator WR…Right direction indicator

Claims

1. A driving assistance device for a vehicle that can perform at least lane keeping control to make the vehicle travel along a travel lane, and obstacle avoidance control to set a travel route to avoid obstacles on a road and make the vehicle travel along the travel route, a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; an obstacle estimation unit that estimates the presence of an obstacle ahead based on the behavior distribution of a plurality of preceding vehicles recognized by the surrounding environment recognition device, and, when the presence of the obstacle is estimated, estimates the position and area where the obstacle exists; a path calculation unit that calculates a plurality of candidate path areas along which the vehicle travels while avoiding the estimated obstacle; a path selection unit that selects and sets an appropriate path area from the calculated plurality of path areas; a travel control unit for controlling travel of the vehicle along the set travel path area; Equipped with the plurality of preceding vehicles are at least two preceding vehicles traveling on the same lane as the vehicle, The behavior distribution is calculated based on a lateral position change amount when the at least two preceding vehicles deviate laterally from a virtual center line of the driving lane. A vehicle driving assistance device characterized by:

2. The driving control unit further includes a path adjustment unit that adjusts the position of the selected path area in accordance with the surrounding environment of the vehicle.

2. The vehicle driving assistance device according to claim 1.

3. The surrounding environment recognition device includes an in-vehicle camera device that acquires image data of the surroundings of the vehicle and recognizes the surrounding environment of the vehicle, and an in-vehicle radar device that outputs radio waves to the surroundings of the vehicle, receives reflected waves from objects, and analyzes the received waves to recognize the surrounding environment of the vehicle.

3. The vehicle driving assistance device according to claim 1 or 2.

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