Driving assistance device and driving assistance program

Abstract

A driving assistance device (40) comprises: a travel trajectory calculation unit (42) for, on the basis of periphery monitoring information for a vehicle (60) acquired from a periphery monitoring device (20), executing driving assistance for the vehicle and calculating a travel trajectory of the vehicle; an operation region calculation unit (43) for calculating an operation region around the vehicle on the basis of the travel trajectory of the vehicle calculated by the travel trajectory calculation unit; a traffic lane change detection unit (46) for detecting a traffic lane change by the vehicle; an operation region correction unit (47) for, when the traffic lane change by the vehicle has been detected by the traffic lane change detection unit, correcting the operation region on the basis of traffic lane information concerning a cruising lane after the traffic lane change by the vehicle; and an operation determination unit (48) for, when an object has been detected in the operation region, determining an operation of driving assistance for the vehicle on the basis of the periphery monitoring information.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based on Japanese Application No. 2022-025924, filed on February 22, 2022, the contents of which are incorporated herein by reference. [Technical Field]

[0002] The present disclosure relates to a driving assistance device and a driving assistance program. [Background technology]

[0003] Patent Document 1 describes a driving assistance device that sets an operating area in an adjacent lane different from the lane in which the host vehicle is located, monitors the presence of other vehicles in the operating area, and performs driving assistance. This driving assistance device calculates the host vehicle's traveling trajectory based on odometry information that indicates the operating state of the host vehicle, and estimates the operating area based on the calculated host vehicle traveling trajectory. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-85567 Summary of the Invention

[0005] When the host vehicle travels in a manner that does not follow the vehicle lane shape, such as when changing lanes, the activation area calculated based on the host vehicle's travel trajectory may differ from the lane shape. If the activation area is set to an area where the risk to the host vehicle is low, a vehicle that enters the activation area may activate an alarm or the like, even though the risk to the host vehicle is low.

[0006] In view of the above, an object of the present disclosure is to provide a technology that can appropriately change the operating range when the vehicle travel trajectory does not follow the vehicle line shape.

[0007] The present disclosure provides a driving assistance device that performs driving assistance for a host vehicle based on periphery monitoring information of the host vehicle acquired from a periphery monitoring device. The driving assistance device includes: a driving trajectory calculation unit that calculates a driving trajectory of the host vehicle; an operation area calculation unit that calculates an operation area around the host vehicle based on the driving trajectory of the host vehicle calculated by the driving trajectory calculation unit; a lane change detection unit that detects a lane change of the host vehicle; an operation area correction unit that corrects the operation area based on lane information related to the lane in which the host vehicle will travel after the lane change when the lane change detection unit detects a lane change of the host vehicle; and an operation determination unit that determines activation of driving assistance for the host vehicle when an object is detected within the operation area based on the periphery monitoring information.

[0008] According to the present disclosure, when a lane change of the host vehicle is detected by the lane change detection unit, the activation area correction unit can correct the activation area based on lane information related to the lane the host vehicle will be traveling in after the lane change. Therefore, when the host vehicle's travel trajectory does not follow the vehicle alignment, the activation area can be appropriately changed. For example, an activation area set in an area of ​​low risk to the host vehicle, such as an area that was an adjacent lane before the host vehicle changed lanes but is no longer an adjacent lane after the lane change, can be changed to an activation area that is appropriate for the lane the host vehicle will be traveling in after the lane change. This can prevent the activation determination unit from determining whether to activate the driving assistance function while the activation area remains set in an area of ​​low risk to the host vehicle.

[0009] The present disclosure can also provide a driving assistance program applied to a driving assistance device that performs driving assistance for a host vehicle based on periphery monitoring information of the host vehicle acquired from a periphery monitoring device. This program includes: a traveling trajectory calculation step of calculating a traveling trajectory of the host vehicle; an operation area calculation step of calculating an operation area around the host vehicle based on the traveling trajectory of the host vehicle calculated in the traveling trajectory calculation step; a lane change detection step of detecting a lane change of the host vehicle; an operation area correction step of correcting the operation area based on lane information related to the traveling lane of the host vehicle after the lane change when a lane change of the host vehicle is detected in the lane change detection step; and an operation determination step of determining activation of driving assistance for the host vehicle when an object is detected within the operation area based on the periphery monitoring information.

[0010] According to the driving assistance program, similar to the driving assistance device, the operation area can be appropriately changed when the vehicle's travel path does not follow the vehicle alignment. The operation area set in an area with a low risk to the vehicle can be changed to an operation area that is suitable for the lane the vehicle is traveling in after changing lanes. It is possible to avoid the operation determination unit from determining whether to activate the driving assistance function while the operation area remains set in an area with a low risk to the vehicle. [Brief explanation of the drawings]

[0011] The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which: [Figure 1] FIG. 1 is a block diagram showing a driving assistance system including a driving assistance device according to a first embodiment; [Figure 2] FIG. 2 is a diagram showing an object detection area around the vehicle; [Figure 3] FIG. 3 is a diagram showing a vehicle travel path and an operating region calculated based on the vehicle travel path; [Figure 4] FIG. 4 is a diagram showing the corrected operating region upon detection of a lane change; [Figure 5]FIG. 5 is a flowchart showing a driving assistance process executed by the driving assistance device according to the first embodiment; [Figure 6] FIG. 6 is a diagram showing a change in the distance between the vehicle and a white line when changing lanes; [Figure 7] FIG. 7 is a flowchart showing a driving assistance process executed by the driving assistance device according to the first embodiment; [Figure 8] FIG. 8 is a diagram illustrating how a lane change is detected based on the distance between the vehicle and the road wall. DETAILED DESCRIPTION OF THE INVENTION

[0012] (First embodiment) 1, a driving assistance system 10 according to the embodiment includes a periphery monitoring device 20, odometry sensors 30, an ECU 40, and a controlled device 50. The driving assistance system 10 is mounted on a vehicle, and the ECU 40 functions as a driving assistance device that performs driving assistance for the vehicle based on periphery monitoring information, which is information about the periphery of the vehicle, acquired from the periphery monitoring device 20.

[0013] The periphery monitoring device 20 is configured by devices that acquire periphery monitoring information, which is information about the periphery of the vehicle. The periphery monitoring device 20 includes a radar device 21, a camera device 22, a sonar device 23, and a receiving device 24.

[0014] The radar device 21 is, for example, a known millimeter-wave radar that transmits high-frequency signals in the millimeter wave band. A single radar device 21 may be installed on the vehicle, or multiple radar devices may be installed. The radar device 21 is installed, for example, at the front or rear end of the vehicle, and defines an area within a predetermined detection angle as a detection range in which objects can be detected, and detects the position of an object within the detection range. Specifically, the radar device 21 transmits probe waves at a predetermined cycle and receives reflected waves using multiple antennas. The distance to the object can be calculated based on the transmission time of the probe waves and the reception time of the reflected waves. Furthermore, the relative velocity can be calculated based on the frequency of the reflected waves reflected by the object, which is changed by the Doppler effect. Additionally, the direction of the object can be calculated based on the phase difference between the reflected waves received by the multiple antennas. Note that, if the position and direction of the object can be calculated, the object's position relative to the vehicle can be identified.

[0015] The camera device 22 may be a monocular camera such as a CCD camera, a CMOS image sensor, or a near-infrared camera, or may be a stereo camera. Only one camera device 22 may be installed on the vehicle, or multiple camera devices may be installed. The camera device 22 is attached, for example, at a predetermined height in the center of the vehicle's width direction and captures an image of an area extending in a predetermined angular range toward the front, rear, or side of the vehicle from a bird's-eye view. The camera device 22 extracts feature points indicative of the presence of an object from the captured image. Specifically, edge points are extracted based on the luminance information of the captured image, and a Hough transform is performed on the extracted edge points. In the Hough transform, for example, points on a line where multiple edge points are consecutively arranged, or points where lines intersect at right angles, are extracted as feature points. The camera device 22 sequentially outputs the captured images as sensing information.

[0016] The sonar device 23 is, for example, a radar that uses ultrasonic waves as search waves. It is mounted on the front end, rear end, and both sides of the vehicle and is suitable for measuring the distance to objects around the vehicle. Specifically, for example, the sonar device 23 transmits search waves at a predetermined interval and receives reflected waves using multiple antennas. Multiple detection points on the object are detected based on the transmission time of the search waves and the reception time of the reflected waves, thereby measuring the distance to the object. Additionally, the object's azimuth is calculated based on the phase difference between the reflected waves received by the multiple antennas. Once the distance to the object and the object's azimuth can be calculated, the object's relative position with respect to the vehicle can be identified. Furthermore, the sonar device 23 can calculate the object's relative speed based on the frequency of the waves reflected by the object, which is changed due to the Doppler effect.

[0017] The receiver 24 is a GPS receiver, which is an example of a GNSS (Global Navigation Satellite System) receiver. The receiver 24 can receive positioning signals from a satellite positioning system that determines the current position on the ground using artificial satellites.

[0018] The radar device 21, the camera device 22, the sonar device 23, and the receiving device 24 are examples of the periphery monitoring device 20 that acquires information about the surroundings of the vehicle. In addition to the above, the periphery monitoring device 20 may also include various detection devices and communication devices capable of acquiring information about the surroundings of the vehicle. The periphery monitoring device 20 may include, for example, a sensor that transmits search waves such as LIDAR (Light Detection and Ranging / Laser Imaging Detection and Ranging). It may also include, for example, a communication device related to V2X (Vehicle-to-Everything) communication, including vehicle-to-vehicle communication known as V2V. The periphery monitoring device 20 sequentially outputs detected or received information about objects around the vehicle and the road on which the vehicle is traveling to the ECU 40 as periphery monitoring information.

[0019] The various periphery monitoring devices described above may detect objects not only behind or to the sides of the vehicle 60 but also in front of or to the sides of the vehicle 60 and use the detected objects as position information. The target object to be monitored may be changed depending on the type of periphery monitoring device used. For example, the camera device 22 is suitable for use when the target object is a stationary object such as a road sign or a building, or a moving object such as a pedestrian. The radar device 21 or the sonar device 23 is suitable for use when the target object is an object with a large reflected power. The periphery monitoring device to be used may be selected depending on the type, position, and moving speed of the target object.

[0020] 2 illustrates areas that can be monitored by various surroundings monitoring devices mounted on the vehicle 60. Areas 61FN, 61FL, 61FS, 61BS, and 61B indicated by solid lines indicate areas that can be suitably monitored by the radar device 21 or LIDAR. Areas 62F, 62L, 62R, and 62B indicated by dashed lines indicate areas that can be suitably monitored by the camera device 22. Areas 63F and 63B indicated by dashed lines indicate areas that can be suitably monitored by the sonar device 23.

[0021] Area 61FN is suitable for, for example, parking assist. Area 61FL is suitable for, for example, adaptive cruise control (ACC). Area 61FS is suitable for, for example, emergency braking, pedestrian detection, and collision avoidance. Area 61BS and area 61B are suitable for, for example, rear-end collision warning and blind spot monitoring. Area 62F is suitable for road sign recognition and lane departure warning. Area 62L and area 62R are suitable for perimeter monitoring (surround view). Area 62B is suitable for parking assist and perimeter monitoring.

[0022] The odometry sensors 30 are configured with sensors capable of acquiring odometry information indicating the operating state of the host vehicle. The odometry sensors 30 include a vehicle speed sensor 31, a steering angle sensor 32, and a yaw rate sensor 33. Examples of the odometry information include the vehicle speed, yaw rate, steering angle, and turning radius of the host vehicle 60.

[0023] The vehicle speed sensor 31 is a sensor that detects the traveling speed of the host vehicle 60, and is not limited to, but may be, for example, a wheel speed sensor that can detect the rotation speed of a wheel. The wheel speed sensor used as the vehicle speed sensor 31 is, for example, attached to the wheel portion of the wheel, and outputs a wheel speed signal corresponding to the wheel speed of the vehicle to the ECU 40.

[0024] The steering angle sensor 32 is attached to, for example, a steering rod of the vehicle, and outputs a steering angle signal to the ECU 40 in accordance with a change in the steering angle of the steering wheel in response to an operation by the driver.

[0025] There may be only one yaw rate sensor 33 installed, or there may be multiple yaw rate sensors 33. When only one yaw rate sensor 33 is installed, it is installed, for example, at the center of the host vehicle 60. The yaw rate sensor 33 outputs a yaw rate signal to the ECU 40 according to the rate of change in the steering amount of the host vehicle 60.

[0026] The controlled device 50 is configured to operate based on a control command from the ECU 40 and also by an operational input from the driver. The operational input from the driver may be appropriately processed by the ECU 40 and then input as a control command to the controlled device 50. The controlled device 50 includes, for example, a drive device, a braking device, a steering device, an alarm device, a display device, and the like.

[0027] The drive system is a device for driving the vehicle, and is controlled by the driver's operation of the accelerator or other devices or by commands from the ECU 40. Specifically, examples of the drive system include the vehicle's drive source, such as an internal combustion engine, a motor, or a storage battery, and related components. The ECU 40 has a function to automatically control the drive system in accordance with the driving plan and vehicle state of the host vehicle 60.

[0028] The braking device is a device for braking the vehicle 60, and is composed of a group of devices (actuators) related to brake control, such as sensors, motors, valves, and pumps. The braking device is controlled by the driver's brake operation or by commands from the ECU 40. The ECU 40 determines the timing and amount of braking to apply the brakes, and controls the braking device so that the determined amount of braking is obtained at the determined timing.

[0029] The steering device is a device for steering the host vehicle 60, and is controlled by the driver's steering operation or by commands from the ECU 40. The ECU 40 has a function of automatically controlling the steering device to avoid a collision or change lanes.

[0030] The warning device is a device for notifying the driver, etc., and examples thereof include, but are not limited to, devices that provide an auditory warning, such as a speaker or buzzer, installed in the passenger compartment of the vehicle 60, and devices that provide a visual warning, such as a display. The warning device issues an alarm sound or the like based on a control command from the ECU 40, thereby notifying the driver, for example, of the risk of collision with an object.

[0031] The display device is a device for visually notifying the driver, etc., and is, for example, a display and instruments installed in the cabin of the vehicle 60. The display device notifies the driver, for example, of the risk of collision with an object by displaying a warning message, etc. based on a control command from the ECU 40.

[0032] The controlled device 50 may include devices other than those described above that are controlled by the ECU 40. For example, the controlled device 50 may include a safety device for ensuring the safety of the driver. Specific examples of the safety device include a door lock device that controls the unlocking and locking of vehicle doors, and a seat belt device equipped with a pretensioner mechanism that retracts seat belts provided in each seat of the vehicle 60.

[0033] The ECU 40 includes an information acquisition unit 41, a traveling trajectory calculation unit 42, an operation area calculation unit 43, a white line recognition unit 44, a target recognition unit 45, a lane change detection unit 46, an operation area correction unit 47, and an operation determination unit 48. The ECU 40 includes a CPU, a ROM, a RAM, an I / O, etc., and the CPU executes programs installed in the ROM to realize these functions. As a result, the ECU 40 functions as a driving assistance device that performs driving assistance for the vehicle 60 by creating and outputting control commands to the controlled device 50 based on information acquired from the periphery monitoring device 20 and the odometry sensors 30.

[0034] The information acquisition unit 41 acquires perimeter monitoring information from the perimeter monitoring device 20 and acquires odometry information from the odometry sensors 30. The ECU 40 may include a storage unit for storing various data acquired by the information acquisition unit 41 and values ​​calculated based on the various data. The ECU 40 may further be configured to store a history of the position, rotation angle, etc. of the host vehicle 60 along its travel path, and the position and rotation angle of the host vehicle 60 may be stored in association with each other. The position and rotation angle of the host vehicle 60 can be obtained from detection values ​​of the vehicle speed sensor 31, steering angle sensor 32, yaw rate sensor 33, etc.

[0035] The traveling trajectory calculation unit 42 calculates the traveling trajectory of the host vehicle 60 based on, for example, odometry information acquired from the odometry sensors 30. The traveling trajectory calculation unit 42 may calculate the traveling trajectory of the host vehicle 60 using information other than odometry information. For example, other information such as map information acquired from the receiving device 24 may be used. Specifically, the traveling trajectory calculation unit 42 calculates the traveling trajectory of the host vehicle 60 from a predetermined cycle (e.g., n cycles, where n is a natural number equal to or greater than 2) before the control period T to the present. For example, the traveling trajectory calculation unit 42 calculates an estimated host vehicle position, which is an estimated value of the host vehicle position at each control timing from one cycle before to n cycles before, based on the current position, using the acquired odometry information (values ​​acquired at each control timing up to n cycles before). Then, the traveling trajectory calculation unit 42 calculates a line connecting the current position and the calculated estimated host vehicle position for each cycle as the host vehicle traveling trajectory.

[0036] FIG. 3 exemplarily shows the vehicle travel trajectory when n=12. Points A0 to A12 are points on the travel trajectory of the vehicle 60, and more specifically, represent the midpoints of the line segments connecting the left and right rear wheels of the vehicle 60 at present or in the past. The current position of the vehicle 60 is represented by point A0, and the positions of the vehicle 60 going back in time at predetermined time intervals are represented by points A1, A2, ..., A12. All of points A0 to A12 may be actually measured positions of the vehicle 60, or some of them may be positions calculated by interpolation based on the actual measurement data. When points A0 to A12 are acquired at predetermined time intervals, the distance to each point can be calculated by multiplying the average speed of the vehicle 60 in that section by the time interval.

[0037] Note that odometry information such as the vehicle speed and yaw rate of the host vehicle 60 contains errors due to various factors, such as detection errors and noise from the vehicle speed sensor and yaw rate sensor. Therefore, the system may be configured to calculate an estimated existence range of the host vehicle's estimated position, taking into account errors in the odometry information, for each host vehicle's estimated position at past control timings up to n cycles ago. The estimated existence range can be expressed as an error variance based on the host vehicle's estimated position. Furthermore, by projecting the error variance in the lane width direction (i.e., the direction perpendicular to the direction of travel), the existence probability of the host vehicle's estimated position in the lane width direction can be expressed as a predetermined probability distribution centered on the host vehicle's estimated position. For example, the error variance of the host vehicle's estimated position due to error factors in the odometry information may be modeled as a normal distribution (Gaussian distribution). In this case, the existence probability of the host vehicle's estimated position calculated using the odometry information is the highest peak value in the normal distribution, and the existence probability decreases according to the normal distribution as the distance from the host vehicle's estimated position in the lane width direction increases.

[0038] The operation area calculation unit 43 sets an operation area at least either behind or to the rear side of the vehicle 60. The operation area is set as an area in which, when an object entering the area is detected, driving assistance such as braking, steering, and notification is activated based on predetermined conditions. The operation area can be set to any shape and size within the detection area of ​​the radar device 21. For example, when the operation area is set to the right rear side of the vehicle 60, it is preferable to set it in a strip shape with a width approximately equal to the width of a lane on the right rear side of the vehicle 60, as in the operation area 71R shown in FIG. 3.

[0039] 3, points B0 to B12 and points C0 to C12 are points on lateral lines L0 to L12 that extend in the direction of the turning radius of the vehicle 60 at points A0 to A12, respectively. When i=0 to 12, on the lateral line Li, the distances between points Ai and Bi are all equal and Y1, and the distances between points Bi and Ci are all equal and Y2.

[0040] The operational area calculation unit 43 sets a lateral line Li extending in the normal direction passing through point Ai on the travel trajectory of the host vehicle 60 from the rotation angle θi at point Ai. When the lane width of the host vehicle 60 is SH, the operational area calculation unit 43 estimates the position of point Bi as the left edge of the adjacent lane to the right of the host vehicle 60 and the position of point Ci as the right edge, for example, by setting the intervals Y1 = SH / 2 and Y2 = SH. The operational area calculation unit 43 then estimates the area surrounded by points B0 to B12 and points C0 to C12 as the operational area 71R. The operational area 71R is set to the right of the travel trajectory of the host vehicle 60 as an area of ​​lane width SH that changes along a trajectory similar to the travel trajectory. As shown in FIG. 3, the operational area 71R is set as a shape in which a substantially annular sector-shaped area centered on the rotation center of the host vehicle 60 is connected along the host vehicle travel trajectory. As a result, the operating area 71R becomes smaller toward the inside when the host vehicle 60 is turning, and becomes larger toward the outside.

[0041] The left rear operational area set to the left rear of the host vehicle 60 can also be set or changed in the same way as the operational area 71R, which is the right rear operational area. The operational area calculation unit 43 linearly extends the lateral lines L0-L12 to the left side of the travel trajectory of the host vehicle 60 and sets points D0-D12 and points E0-E12 on the lateral lines L0-L12. Then, the area surrounded by points D0-D12 and points E0-E12 is calculated as the operational area. This makes it possible to set an operational area of ​​lane width SH on the left side of the travel trajectory of the host vehicle 60, which changes along a trajectory similar to the travel trajectory. Note that on the lateral line Li, the distances between points Ai and Di are all equal, SH / 2, and the distances between points Di and Ei are all equal, SH.

[0042] The width of the operational area (width in the lateral line direction) may be set based on the lane width SH of the own lane as described above, or may be set based on the actual lane width of the adjacent lane. The lane width may be measured by detecting white lines using the camera device 22, or may be acquired by the receiving device 26. In the above description, the width of each operational area (width along the lateral line) is defined as the lane width SH, but this is not limiting.

[0043] The operating area calculation unit 43 may set the operating area based on information about the lane in which the vehicle 60 is traveling and the adjacent lanes. For example, the operating area may be set based on information about objects around the vehicle 60 acquired from the camera device 22 (for example, surrounding vehicles and pedestrians, road markings such as dividing lines, road signs, etc.), and position information, geographic information, traffic information, etc. acquired from the receiving device 26.

[0044] The white line recognition unit 44 recognizes the lane markings on the road on which the host vehicle 60 is traveling. The lane markings include various types of lane markings, such as white lines, yellow lines, and double white lines. In this specification, lane markings are sometimes simply referred to as "white lines." Specifically, the white line recognition unit 44 extracts edge points, which are pixels with large variations in brightness, from the image captured by the camera device 22. The white line recognition unit 44 extracts edge points from almost the entire image by repeatedly shifting the position of the edge points in the vertical direction of the image, i.e., the depth direction of the image. By connecting the extracted edge points, white line paint, which is a block of paint constituting the lane markings, is extracted. Note that white line paint is paint that constitutes lines such as dashed or solid white or yellow lines formed on the road in the direction of road extension to divide areas in the width direction of the road. By connecting the extracted white line paint in the direction of travel of the host vehicle 60, lane markings that extend along the direction of travel of the host vehicle 60 are extracted.

[0045] The target recognition unit 45 recognizes targets around the vehicle 60 based on the periphery monitoring information acquired from the periphery monitoring device 20. Specifically, the target recognition unit 45 identifies and recognizes objects as targets based on the size, moving speed, etc. of the object detected around the vehicle 60. The target recognition unit 45 performs target recognition on at least objects detected at least either behind or to the rear side of the vehicle 60.

[0046] The lane change detection unit 46 detects a lane change of the host vehicle 60. A lane change can be detected based on, for example, information about road dividing lines recognized by the white line recognition unit 44, information about road structures obtained by detecting structures around the road, map information obtainable by the receiving device 26, etc. Specifically, for example, the lane change detection unit 46 may be configured to detect a lane change of the host vehicle 60 based on a change in the distance between the host vehicle 60 and a dividing line of the road on which the host vehicle 60 is traveling, which is recognized by the white line recognition unit 44.

[0047] Also, for example, the lane change detection unit 46 may be configured to detect a lane change by the vehicle 60 based on a change in the distance between the vehicle 60 and road structures such as guardrails or road walls installed on the shoulder of the road.

[0048] Furthermore, for example, the lane change detection unit 46 may be configured to detect a lane change of the host vehicle 60 based on map information received by the receiving device 24. Specifically, the shape of the road and lane on which the host vehicle 60 is traveling may be acquired from the map information, and compared with the host vehicle travel trajectory of the host vehicle 60, and if the host vehicle travel trajectory of the host vehicle 60 crosses the lane obtained from the map information, it may be detected that the host vehicle 60 has changed lanes.

[0049] The lane change detection unit 46 may be configured to be able to detect a lane change based on multiple pieces of information, or may be configured to detect a lane change by prioritizing the acquired information. For example, if the lane change detection unit 46 is capable of detecting a lane change based on information about marking lines, information about on-road structures, and map information, it may be configured to detect a lane change based on information about on-road structures and map information when it is difficult to detect a lane change based on information about marking lines.

[0050] When the lane change detection unit 46 detects a lane change of the host vehicle, the operational area correction unit 47 corrects the operational area based on lane information related to the lane the host vehicle 60 will be traveling in after the lane change. The lane information is information related to the lane on which the host vehicle 60 is traveling, including information related to dividing lines, information related to road structures, map information, etc. Correction of the operational area may be performed after the lane change is completed, or may be performed sequentially from the start of the lane change to the completion of the lane change. When a lane change is detected between the point A12 and the point A0 on the host vehicle 60's traveling trajectory shown in FIG. 4, the operational area 71R is corrected to the operational area 72R based on the shape of the lane on which the host vehicle 60 is currently traveling. As shown in FIG. 4, the operational area 72R is a substantially rectangular operational area extending in a direction substantially perpendicular to the current lateral line L0 of the host vehicle 60.

[0051] The corrected operational area 72R may have any shape as long as it follows the shape of the lane on which the host vehicle 60 is currently traveling. For example, the operational area may be changed based on the position of the dividing line separating the left and right edges of the adjacent lane so that it fits within the lane on which the host vehicle 60 is currently traveling. Furthermore, as shown in FIG. 4, for example, the operational area 71R may be corrected to the operational area 72R by moving points A1-A12, B1-B12, and C1-C12, which indicate the past travel path of the host vehicle 60 and the operational area, along lateral lines L1-L12, respectively. The amount of movement (correction amount) of each point can be calculated based on the amount of change in the distance between the host vehicle 60 and the dividing line of the road on which the host vehicle 60 is traveling, as recognized by the white line recognition unit 44. By moving each point based on the correction amount calculated in this manner, the operational area 72R can be corrected to a shape that follows the shape of the lane on which the host vehicle 60 is currently traveling. As shown in Figure 4, points A1 to A12, B1 to B12, and C1 to C12 can be moved from points A0, B0, and C0 on the lateral line L0 of the current vehicle 60 to a lane direction line parallel to the direction of the lane in which the current vehicle 60 is traveling.

[0052] A22 to A32 are obtained by moving points A2 to A12 onto the lane direction line that passes through point A0. B22 to B32 are obtained by moving points B2 to B12 onto the lane direction line that passes through point B0. C22 to C32 are obtained by moving points C2 to C12 onto the lane direction line that passes through point C0. Points A0, A1, A22 to A32 are points on the lane direction line that passes through point A0, and points A0, A1, A22 to A32 are intersections of lateral lines L1 to L12 and the lane direction line that passes through point A0, respectively. Points B0, B1, B22 to B32 are points on the lane direction line that passes through point B0, and points B0, B1, B22 to B32 are intersections of lateral lines L1 to L12 and the lane direction line that passes through point B0, respectively. Points C0, C1, C22 to C32 are points on the lane direction line that passes through point C0, and points C0, C1, C22 to C32 are intersections of lateral lines L1 to L12 and the lane direction line that passes through point C0. The operating region 72R is the diagonally shaded region surrounded by points B0, B1, B22 to B32 and points C0, C1, C22 to C32.

[0053] The operational area correction unit 47 is preferably configured to correct the operational area based on at least image information. The image information is surroundings monitoring information that can be acquired from the camera device 22. The camera device 22 can accurately detect the shape of the lane on which the host vehicle 60 is actually traveling, and correct the operational area to better correspond to the actual vehicle line shape. The operational area correction unit 47 may also be configured to correct the operational area based on at least map information. The map information is surroundings monitoring information that can be acquired from the receiving device 24.

[0054] The operational area correction unit 47 is preferably configured to correct the operational area based on at least the lane marking information. The lane marking information is information about the lane markings of the road on which the host vehicle 60 is traveling. The lane marking information can be obtained by calculation or the like based on the image information that can be obtained from the camera device 22. The lane marking information may also be included in the map information that can be obtained from the receiving device 24.

[0055] The operation region correction unit 47 may be configured not to correct the operation region when the reliability of the lane marking information is low. Alternatively, when the periphery monitoring information includes at least lane marking information, which is information about lane markings on the road on which the host vehicle is traveling, and information other than the lane marking information, the operation region correction unit 47 may be configured to correct the operation region based on information other than the lane marking information when the reliability of the lane marking information is low.

[0056] When the target recognition unit 45 detects an object within the operation area, the operation determination unit 48 issues a command to the controlled device 50 to execute driving assistance control. Examples of driving assistance control include collision prevention control and collision avoidance control, such as a notification command to an alarm device, an automatic braking command to a braking device, and a steering avoidance command to a steering device, and control to activate safety devices, such as a command to automatically lock vehicle doors. The operation determination unit 48 may be configured to determine the operation of various driving assistance systems, such as a secondary collision brake that applies automatic braking to reduce secondary damage when a rear-end collision is unavoidable, a hazard flasher that flashes hazard lights to warn following vehicles of the risk of a rear-end collision, blind spot monitoring that detects vehicles, etc. in blind spots and notifies the driver, a hitch prevention alarm when turning right or left, trailer blind spot monitoring that automatically detects the connection of a trailer and expands the operation area, and a disembarkation alarm that detects vehicles, etc. approaching the host vehicle 60 and notifies the driver to open the door to disembark.

[0057] When the lane change detection unit 46 detects that the host vehicle 60 is changing lanes, the operation range correction unit 47 corrects the operation range based on lane information relating to the driving lane after the host vehicle 60 changes lanes. Therefore, the operation determination unit 48 can appropriately determine the operation of various driving assistance functions of the host vehicle 60 based on the appropriately set operation range.

[0058] As shown in Figures 3 and 4, when the host vehicle 60 meanders due to a lane change, the other vehicle 66 enters the operational area 71R even though it is not traveling in a lane adjacent to the lane the host vehicle 60 is traveling in after the lane change (for example, the other vehicle 66 is traveling in a lane further to the right of the adjacent lane to the right of the host vehicle 60), and thus driving assistance such as control to avoid a collision between the other vehicle 66 and the host vehicle 60 is executed. In contrast, the operational area 72R is corrected to an area extending along the direction of the lane in which the host vehicle 60 is currently traveling. Because the other vehicle 66 does not enter the operational area 72R, it is possible to prevent driving assistance such as control to avoid a collision from being executed.

[0059] On the other hand, even if the host vehicle 60 is meandering, if the meandering follows the shape of the lane, a lane change is not detected and the operational area 71R is not corrected. Therefore, when another vehicle 66 traveling in a lane adjacent to the lane the host vehicle 60 is traveling in enters the operational area 71R, driving assistance such as control to avoid a collision between the other vehicle 66 and the host vehicle 60 is executed.

[0060] Appropriate correction of the activation range also contributes to realizing appropriate activation determination in the various driving assistance systems described above. For example, if the ECU 40 is applied to a hazard flashing system, it can avoid activating the hazard flashing lights even when there is no need to notify the driver, which is useful in countries or regions where there are legal restrictions on hazard flashing lights.

[0061] The ECU 40 executes a driving assistance program, which is a computer program stored in a storage device such as a ROM, to detect an object present within the operation area and control the vehicle. Figure 5 shows a flowchart of the driving assistance process executed by the ECU 40. The process shown in this flowchart is executed continuously at predetermined intervals.

[0062] First, in step S101, odometry information is acquired. For example, detected values ​​of various sensors are appropriately acquired from the vehicle speed sensor 31, steering angle sensor 32, and yaw rate sensor 33, and odometry information related to the traveling state of the host vehicle 60 is acquired. The acquired odometry information is appropriately stored in the ECU 40. The ECU 40 associates the position of the host vehicle 60 with the odometry information and stores them. Then, the process proceeds to step S102.

[0063] In step S102, a host vehicle travel trajectory, which is the travel trajectory of the host vehicle 60, is calculated based on the odometry information stored in the ECU 40. For example, the host vehicle travel trajectory is calculated by linking the past measured positions of the host vehicle 60 with estimated positions between adjacent measured positions estimated based on the odometry information. For example, the host vehicle travel trajectory is calculated as a trajectory obtained by linking points A0 to A12 shown in FIG. 3. Then, based on the calculated host vehicle travel trajectory, an operating area is calculated within the adjacent lane area of ​​the host vehicle 60. For example, points B0 to B12 and points C0 to C12 shown in FIG. 3 are calculated based on the odometry information, and then the process proceeds to step S103.

[0064] In step S103, periphery monitoring information is acquired from at least one of the devices included in the periphery monitoring device 20, such as the radar device 21, the camera device 22, the sonar device 23, and the receiving device 24. Then, the process proceeds to step S104.

[0065] In step S104, white line recognition is performed. Specifically, based on the periphery monitoring information acquired in step S103, the lane markings on the road on which the host vehicle 60 is traveling are recognized, and lane marking information, which is information about the lane markings on the road on which the host vehicle 60 is traveling, is created and stored as part of the periphery monitoring information. Specifically, for example, edge points are extracted from almost the entire area of ​​an image captured by the camera device 22, and the extracted edge points are connected to each other to extract white line paint, which is a block of paint that makes up the lane markings. By connecting the extracted white line paint to each other in the traveling direction of the host vehicle 60, lane markings that exist so as to extend along the traveling direction of the host vehicle 60 are recognized. Then, the process proceeds to step S108.

[0066] In step S108, it is determined whether or not there has been a lane change by the host vehicle 60. For example, a lane change by the host vehicle 60 is detected based on a change in the distance between the host vehicle 60 and the dividing line of the road on which the host vehicle 60 is traveling, which was recognized in step S104.

[0067] FIG. 6 is a diagram showing changes in the distance between the vehicle 60 and a lane marking recognized laterally from the vehicle 60. The "left distance" on the vertical axis indicates the distance between the vehicle 60 and the lane marking on its left side. The "right distance" on the vertical axis indicates the distance between the vehicle 60 and the lane marking on its right side. The horizontal axis indicates the control cycle. The distance W shown in the diagram indicates the sum of the left distance and the right distance when there is almost no change in the left distance and the right distance, and indicates the lane width of the lane in which the vehicle 60 is traveling.

[0068] "Lane Change 1" and "Lane Change 2" in FIG. 6 indicate that the host vehicle 60 has changed lanes from the current driving lane to the lane to its left. In "Lane Change 1," the left distance gradually becomes closer and the right distance becomes farther, then the left and right distances intermittently become zero, and then the left distance intermittently becomes farther and the right distance becomes closer. In "Lane Change 2," the left distance gradually becomes closer and the right distance becomes farther, then the left distance continuously decreases and the right distance increases, and at the point where the left distance turns into the right distance, the left distance intermittently becomes farther. This state indicates that the host vehicle 60 has approached the left lane to change lanes and crossed the left lane marking, causing the left and right lane markings to change. In other words, the lane marking that was recognized as the left lane before the lane change has changed to be recognized as the lane to the right of the host vehicle 60 after the lane change. Furthermore, before the lane change, the lane marking that was the left lane marking in the adjacent lane to the left of the lane the vehicle 60 is traveling in has changed to be recognized as the lane marking on the left side of the vehicle 60. If a lane change has occurred, the process proceeds to step S109. If a lane change has not occurred, the process proceeds to step S110 without performing step S109.

[0069] In step S109, the operational area calculated in step S102 is corrected based on lane information related to the lane the host vehicle 60 will be traveling in after the lane change. For example, if operational area 71R shown in Fig. 3 is calculated in step S102 and it is determined in step S108 that the host vehicle 60 has changed lanes to the adjacent lane on the left, the operational area is corrected based on the shape of the lane the host vehicle 60 is currently traveling on, as in operational area 72R shown in Fig. 4. Points A1 to A12 on the host vehicle travel trajectory shown in Fig. 3 and points B1 to B12 and C1 to C12 that define operational area 71R are calculated based on the amount of change in distance between the host vehicle 60 and the lane markings of the road the host vehicle 60 is traveling on, which were recognized in step S104. For example, in Figure 6, when the left distance and right distance are almost unchanged, the left distance is the fixed left distance WL and the right distance is the fixed right distance WR (i.e., W = WL + WR), the larger the difference between the observed left distance XL and the fixed left distance WL, or the difference between the observed right distance XR and the fixed right distance WR, the larger the correction amount is. By moving each point based on the correction amount calculated in this way, the operating region 72R can be corrected to a shape that follows the shape of the lane on which the host vehicle 60 is currently traveling. Then, proceed to step S110.

[0070] In step S110, target recognition is performed on objects detected around the vehicle 60 based on the surroundings monitoring information acquired in step S103. For example, moving objects such as automobiles, motorcycles, bicycles, and pedestrians, and stationary objects such as road structures are recognized as targets. Then, the process proceeds to step S111.

[0071] In step S111, if the target recognized in step S110 is a target that exists within the operation area, a determination is made to activate driving assist control based on predetermined conditions. If it is determined in step S108 that there is no lane change, if a target exists within operation area 71R, a determination is made as to whether or not to activate driving assist control. If it is determined in step S108 that there is a lane change and the operation area has been corrected in step S109, if a target exists within operation area 72R, a determination is made as to whether or not to activate driving assist control. If it is determined that the driving assist control should be activated, a command is issued to controlled device 50 to execute driving assist control.

[0072] As described above, the processing related to this driving assistance program includes a driving trajectory calculation step (corresponding to step S102) for calculating the driving trajectory of the host vehicle, an operation area calculation step (corresponding to step S102) for calculating an operation area around the host vehicle based on the driving trajectory of the host vehicle calculated in the driving trajectory calculation step, a lane change detection step (corresponding to step S108) for detecting a lane change of the host vehicle, an operation area correction step (corresponding to step S109) for correcting the operation area based on lane information regarding the lane in which the host vehicle is traveling after changing lanes when a lane change of the host vehicle is detected in the lane change detection step, and an operation determination step (corresponding to step S111) for determining whether to activate driving assistance for the host vehicle when an object is detected within the operation area based on surrounding monitoring information.

[0073] According to the driving assistance process of the first embodiment, as shown in steps S101 and S102, the host vehicle 60's own vehicle travel trajectory is calculated based on the odometry information acquired from the odometry sensors 30, and the operating region 71R around the host vehicle 60 is calculated based on the calculated host vehicle travel trajectory of the host vehicle 60. Using the actual measured position of the host vehicle 60 and an estimated position obtained by estimating the position of the host vehicle 60 using the odometry information, the host vehicle's travel trajectory can be calculated with high accuracy, and therefore the operating region 71R can be calculated with high accuracy.

[0074] Furthermore, as shown in steps S103, S104, and S108, a lane change of the host vehicle 60 is detected based on periphery monitoring information acquired from the periphery monitoring device 20. When a lane change is detected, as shown in step S109, the operation area is corrected to, for example, operation area 72R based on lane information related to the driving lane of the host vehicle 60 after the lane change, and then as shown in steps S110 and S111, the operation of driving assistance for the host vehicle 60 is determined for targets present within the operation area (operation area 72R). The operation area 72R is corrected to an area extending along the direction of the lane in which the host vehicle 60 is currently traveling, and the other vehicle 66 does not enter the operation area 72R, so that it is possible to prevent control to avoid a collision from being executed.

[0075] Furthermore, if a lane change is not detected, step S109 is not executed, and the process proceeds to steps S110 and S111, where a determination is made as to whether or not to activate driving assistance for the host vehicle 60 with respect to a target that exists within the operation area (operation area 71R). For example, even if the host vehicle 60 meanders as shown in FIG. 3, if the meandering follows the shape of the lane, a lane change is not detected, and therefore the operation area 71R is not corrected. Therefore, when another vehicle 66 traveling in a lane adjacent to the lane in which the host vehicle 60 is traveling enters the operation area 71R, driving assistance such as control for avoiding a collision between the other vehicle 66 and the host vehicle 60 can be appropriately executed.

[0076] (Second embodiment) Fig. 7 shows a flowchart of the driving assistance process according to the second embodiment. The driving assistance process shown in Fig. 7 differs from the driving assistance process shown in Fig. 5 in that, as shown in steps S204 to S207, a method for detecting a lane change is selected based on the reliability of white line recognition. The processes shown in steps S201 to S203 and S208 to S211 are similar to the processes shown in steps S101 to S103 and S108 to S111, and therefore will not be described.

[0077] After acquiring perimeter monitoring information in step S203, the process proceeds to step S204, where white line information, i.e., lane line information, is acquired. Next, in step S205, it is determined whether the reliability of the lane line information acquired in step S204 is high. Specifically, it is determined whether the reliability of the lane line information is equal to or greater than a predetermined threshold. If the reliability is equal to or greater than the predetermined threshold, the white line reliability is deemed high, and the process proceeds to step S206, where lane change detection is performed based on the lane line information. If the reliability is less than the predetermined threshold, the white line reliability is deemed low, and the process proceeds to step S207, where lane change detection is performed based on perimeter monitoring information other than the lane line information. Specifically, for example, a lane change of the host vehicle 60 is detected based on a change in the wall distance, which is the distance between the host vehicle 60 and the road wall.

[0078] FIG. 8 shows a case where a vehicle 60 changes lanes from lane 82 to lane 83 on a road 80 having lanes 81 to 84. Vehicle 60a indicates the position of vehicle 60 before the lane change, and vehicle 60b indicates the position of vehicle 60 after the lane change. Road walls 85 and 86 are installed at both ends of road 80, and each of lanes 81 to 84 is divided by a dividing line 87. The distance from the position of vehicle 60a to the left road wall 86 is X1, and the distance from the position of vehicle 60b to the left road wall 86 is X2. A lane change can be detected by detecting a change in the distance from the road wall from X1 to X2.

[0079] After steps S206 and S207, the process proceeds to step S208, and if a lane change has occurred, the process proceeds to the following step S209. If a lane change has not occurred, the process proceeds to step S210 without performing step S209.

[0080] In step S209, the operational area calculated in step S202 is corrected based on lane information related to the lane in which the host vehicle 60 will be traveling after changing lanes. For example, in step S202, operational areas 73R and 73L shown in Fig. 8 are calculated, and if it is determined in step S208 that the host vehicle 60 has changed lanes to the adjacent lane on the left, the operational area is corrected based on the shape of the lane in which the host vehicle 60 is currently traveling, as in operational areas 74R and 74L shown in Fig. 4.

[0081] When detecting a lane change based on lane marking information, in step S209, similar to step S109 shown in Fig. 5, the amount of correction to the operating region is calculated based on the amount of change in the distance between the vehicle 60 and the lane marking of the road on which the vehicle 60 is traveling. When detecting a lane change by the vehicle 60 based on the amount of change in the wall distance, in step S209, the amount of correction to the operating region is calculated based on the amount of change in the wall distance. Thereafter, similar to the flowchart shown in Fig. 5, the processes of steps S210 to S211 are executed, and then the driving assistance process ends.

[0082] According to the driving assistance process of the second embodiment, as shown in steps S205 to S207, when the reliability of the lane marking information is low, the operating region is corrected based on information other than the lane marking information. Information such as the position and shape of the lane marks included in the lane marking information more accurately reflects the shape of the lane on which the host vehicle 60 is traveling compared to information other than the lane marking information. Therefore, when the reliability of the white lines is high, the lane marking information is used preferentially to detect lane changes. This allows the shape of the lane on which the host vehicle 60 is traveling to be detected with high accuracy. On the other hand, when the reliability of the white lines is low, information other than the lane marking information is used to detect lane changes. This allows the shape of the lane on which the host vehicle 60 is traveling to be detected based on information other than the lane marking information, even in a situation where the accuracy of white line recognition is reduced, for example, when the accuracy of the camera device 22 is reduced, to detect a lane change by the host vehicle 60.

[0083] In the flowchart shown in FIG. 7, if it is determined in step S205 that the reliability of the lane marking information is low, the process proceeds to step S207, where a lane change is detected based on information other than the lane marking information. However, this is not limited to this. For example, if it is determined in step S205 that the reliability of the lane marking information is low, the process may not correct the operating region. Specifically, if it is determined in step S205 that the reliability of the lane marking information is low, the process may proceed to step S210. Furthermore, if it is determined in step S205 that the reliability of the lane marking information is low, the reliability of information other than the lane marking information may also be evaluated. A lane change may be detected based on highly reliable information other than the lane marking information, or if the reliability of any information is not sufficiently high or if information other than the lane marking information is unavailable, the process may not correct the operating region.

[0084] In the above-described embodiments, examples have been described in which band-shaped operation areas 71R, 72R are set on the right rear side of the host vehicle 60, but the present invention is not limited to this. The size, shape, and set position of the operation area calculated by the operation area calculation unit 43 and the operation area corrected by the operation area correction unit 47 are changed depending on specific driving assistance such as a warning command to an alarm device, an automatic braking command to a braking device, collision prevention control or collision avoidance control, control to activate a safety device, secondary collision braking, hazard flashing that flashes hazard lights to warn following vehicles of the risk of a rear-end collision, blind spot monitoring that detects vehicles or the like in a blind spot and notifies the driver, hitch-in prevention warning when turning right or left, trailer blind spot monitoring that automatically detects the connection of a trailer and expands the operation area, and a dismount warning that detects vehicles or the like approaching the host vehicle 60 and notifies the driver to open the door to dismount.

[0085] According to each of the above embodiments, the following effects can be obtained.

[0086] The ECU 40 functions as a driving assistance device that performs driving assistance for the vehicle 60 based on the surrounding monitoring information of the vehicle 60 obtained from the surrounding monitoring device 20, and is equipped with a driving trajectory calculation unit 42, an operating area calculation unit 43, a white line recognition unit 44, a lane change detection unit 46, an operating area correction unit 47, and an operation determination unit 48.

[0087] The travel trajectory calculation unit 42 calculates the travel trajectory of the host vehicle 60. The operation area calculation unit 43 calculates an operation area (e.g., operation area 71R) around the host vehicle 60 based on the travel trajectory of the host vehicle 60 calculated by the travel trajectory calculation unit 42. The lane change detection unit 46 detects a lane change of the host vehicle 60. When the lane change detection unit 46 detects a lane change of the host vehicle 60, the operation area correction unit 47 corrects the operation area to, for example, operation area 72R based on lane information related to the travel lane of the host vehicle 60 after the lane change. When an object is detected within the operation area (operation area 71R or operation area 72R), the operation determination unit 48 determines the operation of the driving assistance of the host vehicle 60. The above-mentioned units included in the ECU 40 make it possible to appropriately change the operation area when the host vehicle's travel trajectory does not follow the vehicle alignment. For example, an operation area (e.g., operation area 71R) set in an area with low risk to the host vehicle 60, such as an area that was an adjacent lane before the host vehicle 60 changed lanes but is no longer an adjacent lane after the lane change, can be changed to an operation area (e.g., operation area 72R) that is adapted to the shape of the vehicle alignment after the host vehicle 60 has changed lanes. As a result, it is possible to avoid the operation determination unit 48 from determining whether to operate the driving assistance while the operation area remains set in an area with low risk to the host vehicle 60.

[0088] The surroundings monitoring information may include image information of the surroundings of the vehicle 60 captured by the camera device 22. In this case, the operational area correction unit 47 is preferably configured to correct the operational area based at least on the image information. The camera device 22 can accurately detect the shape of the lane on which the vehicle 60 is actually traveling, and correct the operational area to one that more closely corresponds to the actual vehicle line shape.

[0089] The surroundings monitoring information may include map information received by the receiving device 24. In this case, the operation area correction unit 47 may be configured to correct the operation area based on at least the map information.

[0090] The surroundings monitoring information may include lane marking information, which is information about lane markings on the road the vehicle is traveling on. In this case, the operating area correction unit 47 is preferably configured to correct the operating area based on at least the lane marking information.

[0091] The operation region correction unit 47 may be configured not to correct the operation region when the reliability of the lane marking information is low. Alternatively, when the periphery monitoring information includes at least lane marking information, which is information about lane markings on the road on which the host vehicle is traveling, and information other than the lane marking information, the operation region correction unit 47 may be configured to correct the operation region based on information other than the lane marking information when the reliability of the lane marking information is low.

[0092] The traveling trajectory calculation unit 42 is preferably configured to calculate the traveling trajectory of the host vehicle 60 based on odometry information that indicates the operating state of the host vehicle 60. In addition to the actually measured position of the host vehicle 60, the position of the host vehicle 60 can be calculated interpolatively based on the odometry information, so that the host vehicle traveling trajectory can be calculated with high accuracy.

[0093] The driving assistance program applied to ECU 40 includes a driving trajectory calculation step for calculating the driving trajectory of the host vehicle, an operation area calculation step for calculating an operation area around the host vehicle based on the driving trajectory of the host vehicle calculated in the driving trajectory calculation step, a lane change detection step for detecting a lane change of the host vehicle, an operation area correction step for correcting the operation area based on lane information regarding the lane in which the host vehicle will be traveling after changing lanes if a lane change of the host vehicle is detected in the lane change detection step, and an operation determination step for determining whether to activate driving assistance for the host vehicle if an object is detected within the operation area based on surrounding monitoring information.

[0094] The controller and methods described herein may be implemented by a special-purpose computer configured with a processor and memory programmed to perform one or more functions embodied in a computer program. Alternatively, the controller and methods described herein may be implemented by a special-purpose computer configured with a processor configured with one or more dedicated hardware logic circuits. Alternatively, the controller and methods described herein may be implemented by one or more special-purpose computers configured with a processor and memory programmed to perform one or more functions in combination with a processor configured with one or more hardware logic circuits. Furthermore, the computer program may be stored as instructions executed by a computer on a computer-readable non-transitory storage medium.

[0095] Although the present disclosure has been described with reference to the embodiments, it is understood that the present disclosure is not limited to the embodiments or structures. The present disclosure also encompasses various modifications and equivalent modifications. In addition, various combinations and forms, including only one element, more than one element, or less than one element, are also within the scope and spirit of the present disclosure.

[0096] The following describes characteristic configurations extracted from the above-described embodiments. [Configuration 1] A driving assistance device (40) that performs driving assistance for a vehicle (60) based on surroundings monitoring information of the vehicle (60) acquired from a surroundings monitoring device (20), a travel trajectory calculation unit (42) for calculating a travel trajectory of the vehicle; an operational area calculation unit (43) that calculates an operational area around the host vehicle based on the traveling trajectory of the host vehicle calculated by the traveling trajectory calculation unit; a lane change detection unit (46) for detecting a lane change of the host vehicle; an operation area correction unit (47) that corrects the operation area based on lane information regarding the driving lane of the host vehicle after the lane change, when the lane change detection unit detects a lane change of the host vehicle; and an operation determination unit (48) that determines operation of driving assistance for the host vehicle when an object is detected within the operation area based on the surrounding monitoring information. [Configuration 2] The surroundings monitoring information includes image information of the surroundings of the vehicle captured by a camera device (22), 2. The driving assistance device according to claim 1, wherein the operational range correction unit corrects the operational range based on at least the imaging information. [Configuration 3] The surrounding area monitoring information includes map information received by a receiving device (24), 3. The driving assistance device according to claim 1, wherein the operation range correction unit corrects the operation range based on at least the map information. [Configuration 4] the surroundings monitoring information includes lane marking information that is information about lane markings on a road on which the host vehicle is traveling, The driving assistance device according to any one of configurations 1 to 3, wherein the operational region correction unit corrects the operational region based on at least the lane marking information. [Configuration 5] 5. The driving assistance device according to configuration 4, wherein the operation region correction unit does not correct the operation region when the reliability of the lane marking information is low. [Configuration 6] the surroundings monitoring information includes at least lane marking information, which is information about lane markings on a road on which the vehicle is traveling, and information other than the lane marking information; The driving assistance device according to any one of configurations 1 to 3, wherein the operational region correction unit corrects the operational region based on information other than the lane marking information when the reliability of the lane marking information is low. [Configuration 7] 7. The driving assistance device according to any one of configurations 1 to 6, wherein the travel locus calculation unit calculates the travel locus of the host vehicle based on odometry information indicating an operating state of the host vehicle. [Configuration 8] A driving assistance program applied to a driving assistance device that performs driving assistance for a host vehicle based on surroundings monitoring information of the host vehicle acquired from a surroundings monitoring device, a travel trajectory calculation step of calculating a travel trajectory of the host vehicle; an operational area calculation step of calculating an operational area around the host vehicle based on the travel path of the host vehicle calculated in the travel path calculation step; a lane change detection step of detecting a lane change of the host vehicle; an operation area correction step of correcting the operation area based on lane information regarding a traveling lane of the host vehicle after the lane change is detected in the lane change detection step; an operation determination step of determining operation of driving assistance for the host vehicle when an object is detected within the operation area based on the periphery monitoring information.

Claims

1. A driving assistance device (40) that performs driving assistance for a vehicle (60) based on surroundings monitoring information of the vehicle (60) acquired from a surroundings monitoring device (20), a travel trajectory calculation unit (42) for calculating a travel trajectory of the vehicle; an operational area calculation unit (43) that calculates an operational area around the vehicle based on the travel path of the vehicle calculated by the travel path calculation unit; a lane change detection unit (46) for detecting a lane change of the vehicle; an operating area correction unit (47) that corrects the operating area based on lane information regarding the driving lane of the host vehicle after the lane change, when the lane change detection unit detects a lane change of the host vehicle; an operation determination unit (48) that determines operation of driving assistance for the host vehicle when an object is detected within the operation area based on the periphery monitoring information, the surroundings monitoring information includes lane marking information that is information about lane markings on a road on which the host vehicle is traveling, The operating region correction unit corrects the operating region based on at least the lane marking information, and does not correct the operating region when the reliability of the lane marking information is low.

2. A driving assistance device (40) that performs driving assistance for a vehicle (60) based on surroundings monitoring information of the vehicle (60) acquired from a surroundings monitoring device (20), a travel trajectory calculation unit (42) for calculating a travel trajectory of the vehicle; an operational area calculation unit (43) that calculates an operational area around the vehicle based on the travel path of the vehicle calculated by the travel path calculation unit; a lane change detection unit (46) for detecting a lane change of the vehicle; an operating area correction unit (47) that corrects the operating area based on lane information regarding the driving lane of the host vehicle after the lane change, when the lane change detection unit detects a lane change of the host vehicle; an operation determination unit (48) that determines operation of driving assistance for the host vehicle when an object is detected within the operation area based on the periphery monitoring information, the surroundings monitoring information includes at least lane marking information, which is information about lane markings on a road on which the vehicle is traveling, and information other than the lane marking information; The operating region correction unit corrects the operating region based on information other than the lane marking information when the reliability of the lane marking information is low.

3. The surroundings monitoring information includes image information of the surroundings of the vehicle captured by a camera device (22), The driving assistance device according to claim 1 or 2, wherein the operational range correction unit corrects the operational range based on the image information.

4. A driving assistance program executed by a computer and applied to a driving assistance device that performs driving assistance for a host vehicle based on surroundings monitoring information of the host vehicle acquired from a surroundings monitoring device, a travel trajectory calculation step of calculating a travel trajectory of the host vehicle; an operational area calculation step of calculating an operational area around the host vehicle based on the travel path of the host vehicle calculated in the travel path calculation step; a lane change detection step of detecting a lane change of the host vehicle; an operation area correction step of correcting the operation area based on lane information regarding a traveling lane of the host vehicle after the lane change is detected in the lane change detection step; an operation determination step of determining operation of driving assistance for the host vehicle when an object is detected within the operation area based on the periphery monitoring information, the surroundings monitoring information includes lane marking information that is information about lane markings on a road on which the host vehicle is traveling, The operating area correction step corrects the operating area based at least on the lane marking information, and the operating area is not corrected if the reliability of the lane marking information is low.

5. A driving assistance program executed by a computer and applied to a driving assistance device that performs driving assistance for a host vehicle based on surroundings monitoring information of the host vehicle acquired from a surroundings monitoring device, a travel trajectory calculation step of calculating a travel trajectory of the host vehicle; an operational area calculation step of calculating an operational area around the host vehicle based on the travel path of the host vehicle calculated in the travel path calculation step; a lane change detection step of detecting a lane change of the host vehicle; an operation area correction step of correcting the operation area based on lane information regarding a traveling lane of the host vehicle after the lane change is detected in the lane change detection step; an operation determination step of determining operation of driving assistance for the host vehicle when an object is detected within the operation area based on the periphery monitoring information, the surroundings monitoring information includes at least lane marking information, which is information about lane markings on a road on which the vehicle is traveling, and information other than the lane marking information; The operation region correcting step corrects the operation region based on information other than the lane marking information when the reliability of the lane marking information is low.

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