JP4661602B2 - Rear vehicle analysis device and collision prediction device - Google Patents

Description

  The present invention relates to a rear vehicle analysis device that analyzes a travel route of a rear vehicle located behind the host vehicle, and a collision prediction device that uses the rear vehicle analysis device.

  In recent years, mainly when the host vehicle is stopped, a vehicle approaching from the rear is detected using a radar device or a camera, and when a collision is predicted, an alarm is given to the driver. Devices for use are known. In such a device, it is necessary to determine whether or not the vehicle approaching from behind collides with the own vehicle when traveling as it is.

As an example of a device that detects a vehicle approaching from behind using a camera, when the host vehicle is traveling in an end lane, the detection of the vehicle on the shoulder side is limited, and various objects existing at the end of the road There is known one in which erroneous detection due to (street trees, signs, etc.) is suppressed (see, for example, Patent Document 1).
JP 2002-104112 A

  However, in the device described in the above-mentioned conventional patent document 1, the positional relationship between the vehicle and the travel lane is not taken into consideration. For this reason, when a vehicle approaching from behind travels as it is, it may not be possible to appropriately determine whether or not it collides with the host vehicle.

  For example, when the host vehicle has a yaw angle with respect to the traveling lane, such as when waiting for a right turn at an intersection, in this case, along the traveling direction of the vehicle (the direction along the central axis in the vehicle width direction) When a vehicle behind is detected, the detection range is extended obliquely with respect to the traveling lane on the road. Therefore, the detected vehicle is not necessarily a vehicle that collides with the host vehicle when traveling as it is.

  In addition, there may be a case where the host vehicle is close to either end in the driving lane. In this case, the driving route and the driving lane on the road that are considered to collide with the host vehicle when the vehicle is driven as it is Deviation occurs. Therefore, if detection is performed along a traveling lane on a road recognized by a camera or the like, the detected vehicle is not necessarily a vehicle that collides with the own vehicle when traveling as it is.

  The present invention is for solving such a problem, and a rear vehicle capable of appropriately analyzing a travel route of a rear vehicle located behind the host vehicle in consideration of the positional relationship between the vehicle and the travel lane. It is a main object to provide an analysis apparatus and a collision prediction apparatus that can appropriately predict a collision from behind by using the analysis apparatus.

  In order to achieve the above object, a first aspect of the present invention is a rear vehicle analysis device that analyzes a travel route of a rear vehicle located behind the host vehicle, and detects a positional relationship between the travel lane and the host vehicle. Position relation detection means, rear vehicle information acquisition means for acquiring information related to the rear vehicle, position relation between the traveling lane and the own vehicle detected by the position relation detection means, and the rear vehicle acquired by the rear vehicle information acquisition means And a predetermined rear region probability estimating means for estimating, as a predetermined rear region probability, a probability that the rear vehicle is traveling in a predetermined rear region extending behind the host vehicle based on the information on To do.

  According to the first aspect of the present invention, it is possible to appropriately analyze the travel route of the rear vehicle positioned behind the host vehicle in consideration of the positional relationship between the vehicle and the travel lane.

  Further, in the first aspect of the present invention, the predetermined rear region is, for example, along the travel lane centering on a straight line extending from the center of the rear end of the vehicle in the vehicle width direction along the travel lane to the rear of the vehicle. This is an extended area.

  Further, in the first aspect of the present invention, the positional relationship detection means determines, for example, the yaw angle of the host vehicle with respect to the travel lane and the displacement of the host vehicle in the travel lane width direction, and the positional relationship between the travel lane and the host vehicle. It is a means to detect as.

  Further, in the first aspect of the present invention, the predetermined rear region probability estimation unit is, for example, a travel lane detected by the positional relationship detection unit with respect to a range in which the rear vehicle information acquisition unit acquires information on the rear vehicle. And a means for estimating the predetermined rear region probability by applying a predetermined probability map created based on the positional relationship between the vehicle and the host vehicle.

  Further, in the first aspect of the present invention, the predetermined rear region probability estimation unit includes, for example, a travel lane detected by the positional relationship detection unit in a range in which the rear vehicle information acquisition unit acquires information about the rear vehicle. It is means for estimating the predetermined rear region probability by applying a predetermined probability map to a part selected based on the positional relationship of the host vehicle.

  Further, in the first aspect of the present invention, the rear vehicle information acquisition means has a range for acquiring information related to the rear vehicle based on the positional relationship between the traveling lane and the host vehicle detected by the positional relationship detection means, for example. It can be changed.

  In the first aspect of the present invention, the positional relationship detection means includes, for example, an imaging means for imaging the periphery of the vehicle, and detects the positional relationship between the traveling lane and the host vehicle based on the image from the imaging means. Means.

  In addition, the first aspect of the present invention includes, for example, a steering angle detection unit that detects a steering angle of a vehicle, and a vehicle speed detection unit that detects a vehicle speed. Based on the detected value of the positional relationship detecting means, the steering angle of the vehicle detected by the steering angle detecting means, and the positional relationship between the future traveling lane and the own vehicle predicted based on the vehicle speed detected by the vehicle speed detecting means. The means for estimating the predetermined rear region probability.

  In the first aspect of the present invention, for example, the vehicle includes a steering angle detection unit that detects a steering angle of the vehicle and a vehicle speed detection unit that detects a vehicle speed, and the predetermined rear region probability estimation unit preferably includes: First estimation mode for estimating the predetermined rear region probability based on the detection value of the positional relationship detection means, the detection value of the positional relationship detection means, the steering angle of the vehicle detected by the steering angle detection means, and the vehicle speed detection It is a means which can switch between the 2nd estimation mode which estimates the predetermined back area | region probability based on the future driving | running | working lane predicted based on the vehicle speed detected by the means, and the positional relationship of the own vehicle.

  Further, in the first aspect of the present invention, the predetermined rear region probability estimation means is means for switching between the first estimation mode and the second estimation mode based on the vehicle speed detected by the vehicle speed detection means. Alternatively, it may be a means for switching between the first estimation mode and the second estimation mode based on the vehicle speed detected by the vehicle speed detection means and the steering angle detected by the steering angle detection means.

  Moreover, in this 1st aspect of this invention, a back vehicle information acquisition means contains the radar apparatus which can detect the distance, speed, and direction of the back vehicle from the own vehicle, for example.

  In the first aspect of the present invention, the positional relationship detection means preferably includes virtual lane setting means for setting a virtual travel lane in an area where the travel lane is unknown, and for an area where the travel lane is unknown, It is a means for detecting the positional relationship between the traveling lane and the host vehicle by complementing with the virtual lane set by the virtual lane setting means.

  According to a second aspect of the present invention, there is provided the rear vehicle analysis device according to the first aspect of the present invention, and the rear vehicle is based on the predetermined rear region probability estimated by the predetermined rear region probability estimation means included in the rear vehicle analysis device. It is a collision prediction apparatus which performs the prediction regarding the collision to the own vehicle.

  According to the present invention, it is possible to provide a rear vehicle analysis device capable of appropriately analyzing a travel route of a rear vehicle located behind the host vehicle in consideration of the positional relationship between the vehicle and the travel lane, and It is possible to provide a collision prediction apparatus that can appropriately predict a collision from the rear by using it.

  Hereinafter, the best mode for carrying out the present invention will be described with reference to the accompanying drawings.

  Hereinafter, an embodiment of a rear vehicle analyzing apparatus according to the present invention and a collision prediction apparatus using the same will be described with reference to FIGS. FIG. 1 is a diagram illustrating an example of the overall configuration of the collision prediction apparatus 1. The collision prediction device 1 has, as main components, a lane recognition device (corresponding to the positional relationship detection means in the claims) 10, a rear vehicle information acquisition device 20, and an electronic control unit for collision prediction device (hereinafter referred to as a collision). 30), a vehicle speed sensor 40, and a steering angle sensor 50. Note that communication between devices in the vehicle in the following description is performed using an appropriate serial communication protocol such as CAN (Controller Area Network).

  The lane recognition device 10 is disposed, for example, at the upper center of the windshield, and includes a front camera 12 and a front camera electronic control unit (hereinafter referred to as a front camera ECU) 14. The front camera 12 is, for example, a CMOS camera, has an optical axis directed obliquely downward in front of the vehicle, and images a road over a range up to several tens [m] ahead of the vehicle. The lane recognition device 10 may be shared with a known lane recognition device used for lane maintenance assist control (lane keeping assist) and lane departure warning control (lane departure warning).

  The front camera ECU 14 is, for example, a computer centered on a CPU, and includes storage means such as a ROM and a RAM and a communication port (hereinafter, various ECUs have the same hardware configuration). The front camera ECU 14 performs binarization processing and feature point extraction processing based on the image captured by the front camera 12, and thus corresponds to a road marking line (white line, yellow line, broken line, botsdots, etc.) on the road. Possible pixels (road lane line candidate points) are selected, and the straight line among the selected road lane line candidate points is recognized as a road lane line. Then, the area defined by the road lane marking is recognized as a lane. In addition to this, it is possible to recognize road marking lines and lanes by various methods. For example, a road shoulder or a median strip may be detected by a method such as pattern matching, and this may be taken into account. Also, in areas where there are no road lane markings (such as in intersections) on the road, virtual lanes are set based on histories of lanes recognized in the past (stored in RAM), etc., and lane recognition is performed. Complement.

  Further, the front camera ECU 14 detects the positional relationship between the lane recognized in the image from the front camera 12 and the host vehicle as described above. Specifically, the vehicle center displacement X (hereinafter referred to as offset) X from the lane edge and the direction (hereinafter referred to as yaw angle) θ of the host vehicle with respect to the lane extending direction are detected and collided. It transmits to ECU30 for prediction apparatuses. FIG. 2 shows an example of how the offset X and yaw angle θ are detected. The offset X is, for example, the difference between the distances x1 and x2 from the central axis M in the left-right direction of the image to the road lane marking (which may be the end of the virtual lane set as described above) at the lower end of the image. Calculated by multiplying by a predetermined count. In addition, the yaw angle θ is, for example, comparing the angles α and β that the road marking line (same as above) has with respect to the image lower end line in the image with the angle when the host vehicle is traveling along the lane. Is calculated by More specifically, the focal length and elevation angle of the front camera 12 may be stored in advance in the ROM of the front camera ECU 14 and the calculation may be performed based on these, or the offset is obtained when the distances x1 and x2 are obtained. A map for deriving X and a map for deriving the yaw angle θ when the angles α and β are obtained may be created in advance and stored in the ROM of the front camera ECU 14 for use.

  The rear vehicle information acquisition device 20 includes, for example, a radar device 22, a rear camera 24, and a rear camera electronic control unit (hereinafter referred to as a rear camera ECU) 26.

  The radar device 22 is, for example, a millimeter wave radar that can detect the distance, speed, and direction of a moving body from the host vehicle. The radar device 22 is fixed, for example, inside a bumper or a trunk room at the rear end of the vehicle body, and detects the distance, speed, and direction of a moving body in a certain detection range extending substantially rearward of the vehicle.

  The rear camera 24 is composed of, for example, a wide angle lens and a CCD camera. The rear camera 24 is disposed on the bumper at the rear end of the vehicle body, the upper part of the license plate, etc., and has an optical axis directed obliquely downward at the rear of the vehicle, and images the rear of the vehicle.

  The rear camera ECU 26 is, for example, a computer centered on a CPU, and includes storage means such as a ROM and a RAM. The rear camera ECU 26 detects a rear vehicle (automobile, two-wheeled vehicle, etc.) by performing binarization processing and feature point extraction processing based on an image captured by the rear camera 24. The rear camera 24 and the rear camera ECU 26 may be used in common with devices used for known back guide monitors.

  In the rear vehicle information acquisition device 20, for example, among the moving bodies detected by the radar device, the distance, speed, and direction from the own vehicle of the vehicle that has been confirmed to be a vehicle by the rear camera 24 and the image processing device 26, The information is transmitted to the ECU 30 for the collision prediction device as information on the rear vehicle. Such a determination may be performed by the rear camera ECU 26, or a separate ECU may be provided. When the rear vehicle is detected by the radar device 22, it is not detected as one point, but actually a plurality of locations of the rear vehicle are detected, and a set of detected locations is recognized as the rear vehicle.

  The collision prediction apparatus ECU 30 includes a probability map creation unit 32, a dynamic correction unit 34, and a collision prediction unit 36 as main functional blocks.

  In the probability map creation unit 32, the probability that the vehicle detected by the rear vehicle information acquisition device 20 is traveling in a predetermined rear region based on information transmitted from the lane recognition device 10 or the rear vehicle information acquisition device 20 is determined. Set a probability map to find.

  The predetermined rear region is a concept used in the process of predicting a collision from the rear, and means a traveling route that is considered to collide with the host vehicle when traveling as it is. In the present embodiment, the predetermined rear region has a width approximately equal to a general road width (for example, 3.5) centering on a straight line extending from the center of the rear end of the host vehicle to the rear of the vehicle along the lane. [M] etc.).

  However, even if a vehicle is detected in the predetermined rear area, there may be cases where it cannot be said that the vehicle is traveling in the predetermined rear area, such as when the vehicle has temporarily passed along with a lane change. Further, as described above, the rear vehicle is not detected as one point by the radar device 22, but a plurality of locations are detected. For example, one point at the end of the rear vehicle is detected within a predetermined rear region. Such a case is also assumed.

  Therefore, if a rear vehicle (including a part of it) is detected at that position, a probability map is created as follows to determine the certainty that it can be said that the vehicle is traveling in a predetermined rear region. is doing.

  FIG. 3 is a diagram illustrating an example of a reference probability map (hereinafter referred to as a reference map). When the vehicle is traveling in the center of the lane along the lane, this reference map may be applied to the area facing the rear of the vehicle. However, when the host vehicle has a yaw angle θ with respect to the lane and the reference map is applied toward the rear of the vehicle, the probability distribution spreads obliquely with respect to the lane as shown in FIG. It becomes. On the other hand, when the own vehicle has an offset X with respect to the lane and the probability map is applied with reference to the lane, the distribution of the probability of the predetermined rear region and the probability is shifted in the lane width direction as shown in FIG. Will be. Therefore, in any case, it is not possible to appropriately detect a vehicle that is considered to collide with the host vehicle when traveling as it is.

  Therefore, in the collision prediction apparatus 1 of the present invention, the yaw angle θ and the adjusted offset X ′ (the displacement from the end of the lane at the center of the rear end of the vehicle, the length of the vehicle with respect to the offset X described above. The probability map is created in consideration of the fact that it can be obtained by adding or subtracting one half multiplied by sin θ. FIG. 5A is a probability map created after changing (shifting) in consideration of the yaw angle θ, and FIG. 5B is after changing (shifting) in consideration of the adjusted offset X ′. This is a created probability map.

  FIG. 6 is a diagram showing a probability distribution when the probability map created in this way is used. As shown in the figure, the probability map is along a predetermined rear region. Accordingly, it is possible to appropriately detect a vehicle that is considered to collide with the host vehicle from behind when traveling as it is. The same effect can be obtained by mechanically changing the detection ranges of the radar device 22 and the rear camera 24. However, as in this embodiment, the detection range is used as it is and the probability map is used as a software. Therefore, since it is not necessary to provide an actuator or the like for mechanically changing the detection range of the radar device 22 or the rear camera 24, the size of the device can be suppressed.

  When the radar device 22 is arranged at the center of the rear end of the vehicle and the predetermined rear region is set with the position of the radar device 22 as a reference (center), the change for the offset X need not be considered.

  The dynamic correction unit 34, in addition to the offset X and the yaw angle θ detected by the lane recognition device 10 when a predetermined condition described later is satisfied, the vehicle speed V and the steering angle sensor 50 detected by the vehicle speed sensor 40. The offset X and the yaw angle θ are corrected in consideration of the steering angle S detected by. Specifically, on the basis of the offset X and the yaw angle θ detected by the lane recognition device 10, the offset X and the yaw angle θ immediately after (near future) are predicted based on the vehicle speed V and the steering angle S, To create the probability map described above.

  In the collision prediction unit 36, based on the probability map set by the probability map creation unit 32, the probability that the detected rear vehicle is traveling in a predetermined rear region, the distance from the host vehicle of the rear vehicle, the speed, Based on the azimuth history, it is predicted whether or not the rear vehicle collides with the host vehicle. Note that this prediction is not limited to an alternative, and may be one that outputs a collision probability, for example.

  Hereinafter, the operation of the collision prediction apparatus 1 will be described. FIG. 7 is a flowchart showing a flow of characteristic processing executed by the ECU 30 for collision prediction device.

  First, the collision prediction device ECU 30 inputs the offset X and yaw angle θ from the lane recognition device 10, the vehicle speed V from the vehicle speed sensor 40, and the steering angle S from the steering angle sensor 50 (S100).

  Next, it is determined whether the vehicle speed V is less than the threshold value V1 and the steering angle S is greater than or equal to the threshold value S1 (S110). This determination is performed to determine whether or not the vehicle is in a situation where the yaw angle of the host vehicle increases and the vehicle leaves the lane, for example, when the vehicle is waiting for a right turn at an intersection. When the host vehicle starts from such a situation, the yaw angle θ and the offset X change suddenly, so the predetermined stop flag is changed to perform dynamic correction. The predetermined stop flag is used to determine whether or not to perform dynamic correction, and 0 is set as an initial value. The threshold value V1 is a small value (for example, 1 to 30 [km / h] or the like) for determining whether or not the vehicle is stopped. Further, the threshold value S1 is set to a value corresponding to the steering operation that is performed before making a right turn or a left turn.

  If the vehicle speed V is less than the threshold value V1 and the steering angle S is greater than or equal to the threshold value S1, 1 is set to the predetermined stop flag (S120).

  Subsequently, as an end condition for the dynamic correction, it is determined whether the host vehicle has deviated from the lane due to a right turn or a left turn, or whether the vehicle speed V is equal to or higher than the threshold value V2 (S130). If any one of these is satisfied, 0 is set to the predetermined stop flag (S140).

  Then, it is determined whether or not the predetermined stop flag is 1 and the vehicle speed V is equal to or higher than V1 (S150).

  If a negative determination is obtained in S150, the probability map is created based on the detection value of the lane recognition device 10 without performing dynamic correction (S160).

  The creation of the probability map is performed, for example, using the known inverse matrix of the rotation matrix and the adjusted offset X ′ with respect to the reference map as shown in the following equation (1). Here, Rx is the displacement in the x direction (displacement in the lane width direction) from the reference point that is the point that intersects the center of the lane as a result of moving the center of the host vehicle in the lane width direction, and Ry is the above reference The displacement in the y direction from the point (displacement along the lane longitudinal direction) is represented respectively. M (Rx, Ry) represents the probability derived by applying the reference map to the coordinates (Rx, Ry), and M ′ (Rx, Ry) represents the adjusted offset X ′ and the yaw angle θ. Represents the probability derived from the coordinates (Rx, Ry) using the map modified using.

  M ′ (Rx, Ry) = M (Rx · cos (−θ) −Ry · sin (−θ) −X ′, Rx · sin (−θ) + Ry · cos (−θ)) (1)

  Then, the probability map is applied to the displacement (Px, Py) from the reference point in the rear vehicle to derive the probability that the rear vehicle is traveling in the predetermined rear region. This result can also be expressed as the following equation (2). Therefore, the probability may be derived by directly applying Equation (2) without creating a probability map. Here, P is the distance between the rear vehicle and the reference point.

M ′ (Px, Py) = M (Psin (φ−θ) −X ′, Pcos (φ−θ)) (2)
(However, tanφ = Px / Py)

  As described above, when the radar device 22 is disposed at the center of the rear end of the vehicle and the predetermined rear region is set with the position of the radar device 22 as a reference (center), the offset X and the adjusted offset X ′ are set. This change need not be considered. Accordingly, in the application of the above formulas (1) and (2), Rx and Px represent the displacement in the x direction from the host vehicle, and Ry and Py represent the displacement in the y direction from the host vehicle, respectively. Both formulas may be replaced with those obtained by deleting the X ′ portion. The same applies to the processing of S180 described later.

  If a positive determination is obtained in S150, the offset X and yaw angle θ after time T are predicted based on the vehicle speed V and the steering angle S (S170), and the above equation (1) is applied to this predicted value. Then, a probability map is created (S180). That is, dynamic correction is performed. The time T is, for example, a time of about 0 comma number [sec] to several [sec]. Specifically, in the dynamic correction, when a vehicle speed V and a steering angle S are given, a map for deriving a change amount of an offset or a yaw angle is stored in advance, and the change amount obtained by using this is calculated as follows: This is performed by adding to the currently recognized offset X and yaw angle θ. Further, for the sake of more accuracy, it may be compared and verified with the detection value of the lane recognition device 10 every predetermined time (cycle), and if the deviation from the detection value is large, it may be corrected again to the detection value side. .

  As described above, the dynamic correction is started when the host vehicle starts (V ≧ V1) in a state where the host vehicle stops (V <V1) and the steering angle S is cut by a predetermined angle (S1) or more. When the vehicle speed V becomes V2 or higher or turns right and left and leaves the lane, the process ends (S110 to S150). In such a situation, since the offset X and the yaw angle θ change relatively quickly, the processing speed of processing the image of the front camera 12 and calculating the offset X and the yaw angle θ may not be sufficient to cope with the change. Arise. On the other hand, since the detection speed of the vehicle speed V and the steering angle S is generally faster than that of the image processing, it is possible to quickly cope with a situation where the offset X and the yaw angle θ change relatively quickly. .

  When a probability map is created by the processing of S160 or S180, a predetermined rear region probability is derived based on the probability map (S190).

  Then, based on the predetermined rear region probability, prediction regarding the collision of the rear vehicle with the host vehicle is performed (S200). This prediction may predict, for example, whether or not to collide, or may calculate the possibility of collision. Specifically, for example, it can be performed by multiplying a predetermined rear region probability by a predetermined coefficient obtained as a function of the distance, speed, and direction history of the vehicle behind the host vehicle. As described above, since the predetermined rear region probability that the vehicle behind the vehicle is traveling in the predetermined rear region can be obtained appropriately, the prediction regarding the collision can be performed more appropriately.

  When the prediction about the collision of the rear vehicle with the own vehicle is performed, various controls can be performed based on the prediction. For example, driving the assist motor of the steering device to change the steering angle or issuing a collision warning to the occupant can be considered. However, since this control does not form the core of the present invention, a detailed description is omitted.

  Thus, according to the collision prediction apparatus 1 according to the present embodiment, since the probability map is created using the offset X and the yaw angle θ, the probability map matches the predetermined rear region, and when the vehicle travels as it is, the own vehicle It is possible to appropriately detect a vehicle traveling on a traveling path that collides with the vehicle from behind. In addition, it is possible to suppress an increase in the size of the device as compared with a device in which the detection range of the radar device 22 and the rear camera 24 is mechanically variable.

  Further, in a situation where the offset X and the yaw angle θ change relatively quickly, the offset X and the yaw angle θ are relatively fast because dynamic correction is performed using the vehicle speed V and the steering angle S that can be detected at a faster speed. It can respond quickly to changing conditions.

  In addition, since the predetermined rear region probability can be appropriately obtained as described above, the prediction regarding the collision can be performed more appropriately.

  In the configuration of the collision prediction device 1 according to the present embodiment, the lane recognition device 10, the rear vehicle information acquisition device 20, and the probability map creation unit 32 among the functional blocks of the collision prediction device ECU 30 are the present invention. The rear vehicle analysis apparatus is configured.

  As mentioned above, although the best mode for carrying out the present invention has been described using one embodiment, the present invention is not limited to such one embodiment, and within the scope not departing from the gist of the present invention, Various modifications and substitutions can be made to the above-described embodiment.

  For example, the shape of the reference map is not limited to that illustrated in the embodiment, and can be arbitrarily set.

  Also, the definition of the predetermined rear region can be arbitrarily changed. For example, a region where the width gradually decreases toward the rear of the host vehicle or a region where the width gradually increases toward the rear of the host vehicle may be used. The reference map may be changed according to this change.

  In addition, the probability map is created based on the offset X and the yaw angle θ. However, the above-described reference map is applied to a portion selected based on the offset X and the yaw angle θ in the detection range, and the predetermined region is set. The probability may be obtained.

  Moreover, although the back vehicle information acquisition apparatus 20 was illustrated as a thing provided with the radar apparatus 22, the back camera 24, and ECU26 for back cameras, it is good also as what acquires the information regarding a back vehicle by either one.

  The lane recognition device 10 detects the positional relationship between the lane and the host vehicle based on the image from the front camera 12, but communicates information detected by an infrastructure such as a radar device installed on the road side. You may acquire by.

  Further, the process of S160 rotates and corrects the displacement (Px, Py) itself from the reference point in the rear vehicle (from the own vehicle when the offset X is not considered as described above) by a known rotation matrix. The adjusted coordinates (Px ′, Py ′) adjusted by the post-offset X ′ may be obtained, and the probability may be derived by applying a reference map to the coordinates.

  The start and end conditions of dynamic correction are not limited to those in the embodiment, and the start and end of dynamic correction may be performed under any conditions. Further, dynamic correction may not be performed, or it may be performed constantly. Furthermore, the detection value of the lane recognition device 10 may be constantly compared and verified using dynamic correction.

  The dynamic correction may be performed by integrating the acceleration in the yaw direction detected by the yaw rate sensor instead of the steering angle S detected by the steering angle sensor.

  The present invention can be used for an apparatus that detects and controls a vehicle from at least the rear. The appearance, weight, size, running performance, etc. of the vehicle to be mounted are not limited.

It is a figure which shows an example of the whole structure of the collision prediction apparatus 1 which concerns on one Example of this invention. It is a figure which shows an example of a mode that the offset X and yaw angle (theta) are detected. It is a figure which shows an example of a reference | standard map. It is a figure which shows distribution of a probability at the time of applying a reference | standard map, when the own vehicle has offset X and yaw angle (theta) with respect to a lane. It is a figure which shows the probability map produced after changing considering the yaw angle (theta) and the offset X. FIG. It is a figure which shows distribution of probability at the time of using the created probability map after changing in consideration of the yaw angle θ and the offset X. It is a flowchart which shows the flow of the characteristic process which ECU30 for collision prediction apparatuses performs.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Collision prediction apparatus 10 Lane recognition apparatus 12 Front camera 14 Front camera electronic control unit 20 Rear vehicle information acquisition apparatus 22 Radar apparatus 24 Rear camera 26 Rear camera electronic control unit 30 Collision prediction apparatus electronic control unit 32 Probability map creation unit 34 Dynamic correction part 36 Collision prediction part 40 Vehicle speed sensor 50 Steering angle sensor

Claims (14)

A rear vehicle analysis device for analyzing a travel route of a rear vehicle located behind the host vehicle,
Positional relationship detection means for detecting the positional relationship between the traveling lane and the host vehicle;
Back vehicle information acquisition means for acquiring information about the back vehicle;
Based on the positional relationship between the traveling lane detected by the positional relationship detection means and the host vehicle, and information on the rear vehicle acquired by the rear vehicle information acquisition unit, the rear vehicle extends behind the host vehicle. A predetermined rear area probability estimating means for estimating a probability of traveling in a predetermined rear area as a predetermined rear area probability;
A rear vehicle analysis device comprising: The rear vehicle analysis device according to claim 1,
The predetermined rear region is a region extending along the traveling lane centering on a straight line extending rearward of the vehicle along the traveling lane from the central portion in the vehicle width direction at the rear end of the vehicle.
Rear vehicle analysis device. The rear vehicle analysis device according to claim 1 or 2,
The positional relationship detection means is means for detecting the yaw angle of the host vehicle with respect to the traveling lane and the displacement of the host vehicle in the traveling lane width direction as the positional relationship between the traveling lane and the host vehicle.
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 3,
The predetermined rear region probability estimation unit is created based on the positional relationship between the traveling lane and the own vehicle detected by the positional relationship detection unit with respect to a range in which the rear vehicle information acquisition unit acquires information on the rear vehicle. Applying a predetermined probability map to estimate the predetermined rear region probability,
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 3,
The predetermined rear region probability estimation unit is selected based on a positional relationship between the traveling lane and the own vehicle detected by the positional relationship detection unit in a range in which the rear vehicle information acquisition unit acquires information on the rear vehicle. A means for applying a predetermined probability map to a part and estimating the predetermined backward region probability.
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 3,
The rear vehicle information acquisition unit is a unit capable of changing a range for acquiring information on the rear vehicle based on the positional relationship between the traveling lane and the host vehicle detected by the positional relationship detection unit.
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 6,
The positional relationship detection means includes imaging means for imaging the periphery of the vehicle, and is means for detecting the positional relationship between the traveling lane and the host vehicle based on an image from the imaging means.
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 7,
Steering angle detection means for detecting the steering angle of the vehicle, and vehicle speed detection means for detecting the vehicle speed,
The predetermined rear region probability estimation means is a future predicted based on the detected value of the positional relationship detection means, the steering angle of the vehicle detected by the steering angle detection means, and the vehicle speed detected by the vehicle speed detection means. A means for estimating the predetermined rear region probability based on a positional relationship between the traveling lane and the host vehicle;
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 7,
Steering angle detection means for detecting the steering angle of the vehicle, and vehicle speed detection means for detecting the vehicle speed,
The predetermined backward region probability estimation means is
A first estimation mode for estimating the predetermined rear region probability based on a detection value of the positional relationship detection means;
The positional relationship between the detected value of the positional relationship detecting means, the steering angle of the vehicle detected by the steering angle detecting means, and the future traveling lane and the own vehicle predicted based on the vehicle speed detected by the vehicle speed detecting means. A second estimation mode for estimating the predetermined rear region probability based on
The vehicle analysis apparatus which is a means which can be switched. The rear vehicle analysis device according to claim 9,
The predetermined rear region probability estimation means is means for switching between the first estimation mode and the second estimation mode based on the vehicle speed detected by the vehicle speed detection means.
Rear vehicle analysis device. The rear vehicle analysis device according to claim 9,
The predetermined rear region probability estimation means includes the first estimation mode and the second estimation mode based on the vehicle speed detected by the vehicle speed detection means and the steering angle detected by the steering angle detection means. Is a means of switching
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 11 ,
The rear vehicle information acquisition means includes a radar device capable of detecting the distance, speed, and direction of the rear vehicle from the host vehicle.
Rear vehicle analysis device. The rear vehicle analysis device according to any one of claims 1 to 12,
The positional relationship detection means includes virtual lane setting means for setting a virtual lane in an area where the travel lane is unknown, and the area where the travel lane is unknown is complemented by the virtual lane set by the virtual lane setting means. Is a means for detecting the positional relationship between the traveling lane and the host vehicle,
Rear vehicle analysis device.   A rear vehicle analysis device according to any one of claims 1 to 13, wherein the vehicle of the rear vehicle is based on a predetermined rear region probability estimated by a predetermined rear region probability estimation means included in the rear vehicle analysis device. Collision prediction device that makes predictions about collisions.

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