JP2007099237A - Vehicle drive support device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a vehicle drive support device capable of providing rational drive support that matches any actual outside environment. <P>SOLUTION: An IPU 5 recognizes objects outside a vehicle as outside environment information. A PCU 6 computes the two-dimensional risk potential distribution of each recognized object with respect to one's own vehicle 1, sets a risk map of the outside environment, sets a desired route 61 that continues for a set distance D ahead of the one's own vehicle, with the desired route having a predetermined width W equal to or greater than the preset width of the one's own vehicle, and provides drive support control (deceleration control), based on the risk potential distribution on the desired route 61. In this way, the rational drive support that matches the outside environment can be achieved without the control reflecting obstacles or the like that actually do not much affect the one's own vehicle. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a vehicle driving support device that recognizes an environment outside the vehicle and performs driving support control of the host vehicle based on the recognized vehicle environment information.

Conventionally, there have been many proposals for driving support devices for vehicles that perform driving control of the own vehicle based on external environment information recognized using a monocular camera, stereo camera, millimeter wave radar, laser radar, infrared sensor, etc. Has been made. For example, in Patent Document 1, a risk potential for each obstacle around the host vehicle recognized using a laser radar, a camera, or the like is calculated, and components of each risk potential in the vehicle front-rear direction are extracted and added. The overall left-right risk potential is calculated by extracting and adding the vehicle left-right components of each risk potential, and calculating the overall front-rear risk potential based on the total value of each risk potential. And the technique which calculates the reaction force control amount with respect to the driver operation to the left-right direction is disclosed.
JP 2004-110347 A

  However, when the vehicle control is performed with the overall risk potential of each obstacle, as in the technique disclosed in the above-mentioned Patent Document 1, an obstacle having little influence on the own vehicle is actually added to the control. There is a risk of excessively limiting the behavior of the vehicle.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a vehicle driving support device capable of realizing rational driving support in accordance with an actual vehicle exterior environment.

  The present invention provides a vehicle environment recognition means for recognizing at least an object outside the vehicle as vehicle environment information, and a risk of setting a risk map of the vehicle environment by calculating a two-dimensional risk potential distribution of the respective objects with respect to the vehicle. Map calculation means, target route setting means for setting a target route continuous in a predetermined distance in front of the host vehicle with a predetermined width equal to or greater than a preset vehicle width, and driving of the vehicle based on the risk potential distribution related to the target route Driving assistance control means for performing assistance control is provided.

  According to the vehicle driving support device of the present invention, it is possible to realize rational driving support in accordance with the actual outside environment.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. The drawings relate to an embodiment of the present invention, FIG. 1 is a schematic configuration diagram of a vehicle equipped with a driving support device, FIG. 2 is a functional block diagram showing a schematic configuration of the vehicle driving support device, and FIG. 3 shows a vehicle speed control routine. FIG. 4 is an explanatory diagram showing an example of a risk potential setting map, FIG. 5 is an explanatory diagram showing an example of correcting a risk potential distribution, FIG. 6 is an explanatory diagram showing an example of a risk map, and FIG. It is explanatory drawing which shows a risk potential along the -I line.

  In FIG. 1, reference numeral 1 denotes a vehicle such as an automobile (own vehicle), and a driving assistance device (ADA: Active Drive Assist system) 2 is mounted on the vehicle 1. As shown in FIG. 2, the driving support device 2 includes a stereo camera unit 3, an image processing unit (IPU) 5, a preview control unit (PCU) 6, an engine control unit (ECU) 7, and a vehicle dynamics control unit. (VDC) 8 and an integrated unit 9 are connected to each other through a multiplex communication system such as a CAN (Controller Area Network). The integrated unit 9 includes, for example, a center display 10, a combination meter 11, an audio device 12, a horn 13, and a navigation device 14 via other communication systems (vehicle body side communication systems) having different communication speeds. And are connected.

  The stereo camera unit 3 includes a pair of (left and right) CCD cameras using a solid-state imaging device such as a charge coupled device (CCD). These left and right CCD cameras are each mounted at a predetermined interval in front of the ceiling in the vehicle interior (see FIG. 1), and images the object outside the vehicle from different viewpoints. The stereo camera unit 3 performs A / D conversion, affine conversion, and the like on each image (reference image and comparison image) captured by the left and right CCD cameras, and outputs these image signals to the IPU 5.

The IPU 5 recognizes the environment outside the vehicle based on each image signal from the stereo camera unit 3.
More specifically, the IPU 5 uses a well-known calculation process based on a stereo image and the principle of triangulation, etc., to create a white line on the road, a side wall such as a guardrail or curbstone existing along the road, and a three-dimensional vehicle or the like. Recognize things. That is, the IPU 5 divides the reference image into small areas of 4 × 4 pixels, for example, compares the luminance or color pattern of each small area with the comparison image, finds the corresponding area, and distributes the distance distribution over the entire reference image. Ask for. Further, the IPU 5 examines the luminance difference of each pixel on the reference image with an adjacent pixel (for example, a pixel adjacent on the right side and the lower side), and extracts those having both of the luminance differences exceeding the threshold as edges. At the same time, by providing distance information to the extracted pixel (edge), an edge distribution image (distance image) having the distance information is generated. The IPU 5 recognizes objects such as white lines, side walls, and three-dimensional objects in front of the vehicle by performing a well-known grouping process on the distance image, and assigns different IDs to the recognized data. Are continuously monitored between frames for each ID. Here, the IPU 5 recognizes the three-dimensional object based on, for example, the width and height of the three-dimensional object (the width and height of the grouped pixel group), the relative speed between the three-dimensional object and the vehicle, and the like. Type (pedestrian (adult, child, wheelchair, etc.), bicycle, car, etc.).

  Further, the IPU 6 recognizes the road ahead of the host vehicle based on the information such as the white line and the side wall recognized from the stereo image, the information obtained from the navigation device 14, and the type of the road on which the host vehicle is traveling ( For example, a highway, a general road, a city area, a shopping street, etc.) are identified.

  Further, the IPU 5 estimates the own vehicle traveling lane 60 (see FIG. 6) based on information such as white lines and side walls recognized from the stereo image, traveling state information of the own vehicle 1 obtained from the VDC 8, and the like. For example, when white line data (or side walls, etc.) is obtained in at least one of the left and right in front of the host vehicle, and the shape of the lane in which the host vehicle is traveling can be estimated from these white line data (or side walls, etc.) The IPU 5 estimates the own vehicle traveling lane 60 in parallel with the white line (or side wall or the like). For example, when a preceding vehicle exists ahead of the own vehicle, the IPU 5 can also estimate the own vehicle traveling lane 60 based on the past traveling locus of the preceding vehicle. Further, for example, the IPU 5 can also estimate the own vehicle travel lane 60 based on the driving state (yaw rate, vehicle speed, steering wheel angle, etc.) of the own vehicle.

  Thus, in this embodiment, IPU5 has each function as a vehicle exterior environment recognition means and a own vehicle travel lane estimation means.

  The PCU 6 supervises each function of the driving support device 2, and determines necessity of alarms and various vehicle behavior controls based on information obtained from the IPU 5 and the VDC 8. Then, according to these determination results, the PCU 6 outputs a display signal to the center display 10 and the combination meter 11, and outputs a buzzer (or sound) signal to the speakers 11a and 12a connected to the combination meter 11 and the audio device 12. Various driving support functions are realized by appropriately performing output, outputting control signals to the ECU 7 and the VDC 8, and the like.

  In such driving assistance, the PCU 6 sets a risk map indicating the distribution of risk potential that the outside environment has on the vehicle based on the outside environment information recognized by the IPU 5.

  Specifically, for example, the PCU 6 sets a two-dimensional risk potential distribution according to each object recognized by the IPU 5, and sets a two-dimensional risk potential distribution according to the road type. The risk map of the environment outside the vehicle is set by combining. At that time, the PCU 6 estimates the movement position of each object after a set time t seconds, and corrects the risk potential distribution of each object on the risk map based on the estimated position.

  Further, the PCU 6 sets a target route having a predetermined distance W that is equal to or greater than a preset vehicle width and continuing a set distance D in front of the vehicle. In the present embodiment, the target route is laid (set) while avoiding a region where a high risk potential is distributed on the risk map based on the own vehicle travel lane 60 estimated by the IPU 5, for example.

  Then, the PCU 6 performs driving support control of the vehicle based on the risk potential distribution related to the set target route. For example, the PCU 6 extracts the maximum value of the risk potential, and sets the allowable vehicle speed V0 of the host vehicle so that the higher the maximum value, the lower the speed, and the lower the value, the higher the speed. Then, when the host vehicle speed V exceeds the allowable vehicle speed V0, alarm control that prompts the driver to decelerate, deceleration control of the host vehicle, and the like are performed.

  Thus, in this embodiment, PCU6 implement | achieves each function as a risk map calculation means, a movement position calculation means, a risk map correction means, a target route setting means, and a driving assistance control setting means.

Next, the vehicle speed control executed by the PCU 6 will be described with reference to the flowchart of the vehicle speed control routine shown in FIG.
This routine is repeatedly executed every set time. When the routine starts, first, in step S101, the PCU 6 performs a two-dimensional operation according to the road type recognized by the IPU 5 (the road type on which the vehicle is traveling). Generate a risk potential distribution. That is, in this embodiment, for example, a map (see FIG. 4A) showing a relationship between a road type and a risk potential (risk value P) is preset and stored in the PCU 6. The risk potential based on this map is set uniformly on the road. Further, the PCU 6 sets a risk potential distribution in an area other than the road so that the value increases as the distance from the road increases based on the risk potential on the road (see FIG. 7).

  Here, as shown in FIG. 4A, the risk potential based on the road type is, for example, “0” on a highway where the prospect is relatively good and it is difficult to think of a person jumping out. It is set to a high price as it shifts to a shopping street.

  In subsequent step S <b> 102, the PCU 6 generates a two-dimensional risk potential distribution corresponding to each object recognized by the IPU 5. That is, in the present embodiment, the PCU 6 is preset with a map (see FIG. 4B) for setting a risk potential distribution (risk value P distribution) according to the type of the object, for example. The PCU 6 refers to this map and individually sets the risk potential distribution of each object. For example, as shown in FIG. 5, when the object 50 is an adult person, the PCU 6 sets the risk potential at the center of the object 50 as “100” and the distance from the edge of the object is “0.5 m. ”,“ 1 m ”,“ 1.5 m ”,“ 2 m ”, the risk potential distribution that gradually changes gradually to“ 80 ”,“ 50 ”,“ 20 ”,“ 0 ”is generated. To do.

  Here, as shown in FIG. 4B, the risk potential of each object is set to be distributed over a wider range as the object is more dynamic. For example, even if the person is the same, the risk potential is distributed more widely among children who are actively moving than adults. On the other hand, the risk potential is distributed in a relatively narrow range for a person in a sitting position on a wheelchair or the like. Even for objects other than a three-dimensional object, for example, a slight risk potential is set for a paint that forms a zebra zone or the like.

  In step S103, the PCU 6 combines all the risk potentials generated in steps S101 and S102 to generate a risk map ahead of the host vehicle.

  In the subsequent step S104, the PCU 6 calculates the moving speed v (including the moving direction) of each object based on, for example, a change in the position of each object detected for each frame in the IPU 5, and each calculated movement Based on the speed v, the movement position of each object after the set time t seconds is estimated.

  In step S105, the PCU 6 corrects the risk potential distribution of each object on the risk map based on the movement position of each object estimated in step S104. Specifically, for example, as shown in FIG. 5 (b), the PCU 6 is formed at the movement position where the risk potential distribution similar to the risk potential distribution at the current position of the object 50 is estimated, and at the current position. A continuous risk potential distribution and a risk potential distribution at the estimated movement position are set as the final risk potential distribution of the object 50.

  Thereby, for example, as shown in FIGS. 6 and 7, a risk map of the environment outside the vehicle 1 is set. In FIG. 6, reference numeral 51 denotes a risk potential distribution of a pedestrian (adult person) 51a, reference numeral 52 denotes a risk potential distribution of a car (dynamic) 52a, and reference numeral 53 denotes a pedestrian (child person) 53a. This is the risk potential distribution.

  Here, in order to set a more realistic risk potential distribution, for example, as shown in FIG. 5C, when the risk potential distribution at the current position and the risk potential distribution at the estimated movement position are made continuous, The risk potential distribution at the current position may be reduced by the set gain G. Note that the gain G with respect to the risk potential at the current position can be variably set according to, for example, the distance of the object from the host vehicle 1, the moving speed v of the object, and the like. In this case, for example, the gain G with respect to the risk potential at the current position is set to a smaller value as the object moves away from the own vehicle 1, and is set to a smaller value as the moving speed v of the object increases.

  Here, a specific example of risk potential setting will be described with reference to FIGS. FIG. 7A shows the risk potential related to I-I in FIG. 6. In this case, risk potential distributions 53 and 52 based on the pedestrian 53a and the vehicle 52a, the leftmost guard rail, the white line on the road, and the broken line The risk potential distribution based on the road type and the risk potential distribution based on the road type are set, and the risk potential obtained by adding these risk potentials is distributed.

  FIG. 7B is a risk potential distribution related to II-II in FIG. In this case, risk potential distributions 51 and 52 based on a pedestrian 51a and a vehicle 52a, a risk potential distribution based on the leftmost guard rail, a risk potential distribution based on white lines and broken lines, and a risk potential distribution depending on the road type are set. And the risk potential that is the sum of these risk potentials is distributed.

  FIG. 7C shows a risk potential distribution related to III-III in FIG. In this case, the risk potential distribution based on the leftmost guardrail, the risk potential distribution based on the white line and the broken line, and the risk potential distribution by road type day are set, and the silk potential that is the sum of these risk potentials is distributed. .

  In subsequent step S106, the PCU 6 sets the target route 61 of the host vehicle 1 based on the host vehicle traveling lane 60 estimated by the IPU 5, based on the final risk map set in step S105. In the present embodiment, the target route 61 is formed, for example, as a belt-like region that is continuous by a set distance D while avoiding a region in which a high risk potential is distributed with a predetermined width W that is equal to or greater than the vehicle width. That is, the target route 61 is basically set along the center line of the vehicle lane 60 as shown in FIG. 6, for example, and when there is an area where a high risk potential is distributed in the vicinity, The above area is avoided based on the vehicle driving lane 60. In other words, although the configuration avoids the vehicle traveling lane 60 without departing from the vehicle traveling lane 60, the target route 61 including the vicinity of the outside of the vehicle traveling lane 60 is set as a guide for setting the target route 61. Is also possible. The turning radius of the target route 61 in this case is preferably set so that, for example, the yaw rate generated when traveling along the target route 61 at the current host vehicle speed V is equal to or less than a predetermined value set in advance.

  Here, the distance D of the target route 61 is variably set according to the road type of the road on which the vehicle 1 is traveling. Specifically, for example, the PCU 6 determines that D = 100 m when the road type on which the vehicle 1 is traveling is a highway, D = 40 m when the road is a general road, D = 15 m when the road is an urban area, If it is a town, set D = 10 m.

  In subsequent step S107, the PCU 6 extracts the maximum value Pmax from the risk potential on the target route 61 set in step S106, and sets the allowable vehicle speed V0 of the host vehicle 1 based on the maximum value Pmax of the risk potential. .

Specifically, for example, the maximum speed Vmax allowed for the vehicle is preset in the PCU 6, and the allowable speed can be obtained by subtracting the speed corresponding to the maximum value Pmax of the risk potential from the allowable maximum speed Vmax. The vehicle speed V0 is set. That is, the allowable vehicle speed V0 is set using, for example, equation (1).
V0 = Vmax−k · Pmax (1)
Here, in equation (1), k is a preset speed coefficient. In the present embodiment, Vmax = 100 km / h and k = 1 km / h are set in the PCU 6. For example, when the maximum value of risk potential Pmax = 40, an allowable vehicle speed V0 = 60 km / h is set. The

  In subsequent step S108, the PCU 6 checks whether or not the current host vehicle speed V is higher than the allowable vehicle speed V0 set in step S107. If it is determined in step S108 that the host vehicle speed V is less than or equal to the allowable vehicle speed V0, the PCU 6 directly exits the routine.

  On the other hand, if it is determined in step S108 that the host vehicle speed V is greater than the allowable vehicle speed V0, the PCU 6 proceeds to step S109, and whether the host vehicle speed V is greater than α · V0 (where α is a constant> 1). Check for no.

  If it is determined in step S109 that the host vehicle speed V ≦ α · V0, the PCU 6 proceeds to step S110 and outputs a display signal to the center display 10 and the combination meter 11, the combination meter 11 and the audio device 12. After instructing the driver to decelerate through the output of a buzzer (or sound) signal to the speakers 11a and 12a to be connected, the routine is exited.

  On the other hand, if it is determined in step S109 that the host vehicle speed V> α · V0, the PCU 6 proceeds to step S111, performs deceleration control through output of a control signal to the ECU 7 and VDC 8, etc., and then exits the routine. .

  According to such an embodiment, the object outside the vehicle is recognized as the environment information outside the vehicle, and the risk map of the environment outside the vehicle is set by calculating the two-dimensional risk potential distribution of each recognized object with respect to the vehicle 1. A target route 61 having a predetermined width W equal to or greater than a preset vehicle width is set ahead of the vehicle and a set distance D continues, and driving support control (deceleration control) is performed based on the risk potential distribution on the target route 61. As a result, it is possible to realize rational driving support in accordance with the environment outside the vehicle without reflecting obstacles or the like that have little influence on the vehicle in the control.

  At that time, the movement position of each object after the set time is estimated, and the risk potential distribution of each corresponding object is corrected based on each estimated movement position, thereby rational driving support in accordance with the environment outside the vehicle. Can be realized more effectively.

  Further, by combining the risk potential distribution according to the road type with the risk potential distribution of each target object, it is possible to more effectively realize rational driving support in accordance with the environment outside the vehicle.

  In addition, a realistic target route is set by setting a vehicle lane on the road on the basis of information on the environment outside the vehicle and the vehicle's driving state information, and setting a target route based on the vehicle lane. And more suitable driving support can be realized.

  Here, in the above-described embodiment, an example of performing the deceleration control based on the risk potential distribution on the target route 61 has been described as an example of the driving support control, but the present invention is not limited to this, Acceleration control may be added. Furthermore, a function of performing automatic steering control or the like along the target route may be added.

  In setting the risk map, for example, a map shown in FIG. 4C may be used, and each risk potential on the risk map may be corrected to increase as a whole according to the weather, time zone, or the like.

  Further, in the embodiment, the configuration for correcting the risk potential distribution according to the position of the object is disclosed, but it is also possible to calculate the relative speed with the object and correct based on the relative speed. . In this case, for example, a correction amount based on the relative speed is calculated between steps S105 and S106 in FIG.

Schematic configuration diagram of a vehicle equipped with a driving support device Functional block diagram showing a schematic configuration of a vehicle driving support device Flow chart showing a vehicle speed control routine Explanatory diagram showing an example of risk potential setting map Explanatory drawing showing an example of correction of risk potential distribution Explanatory diagram showing an example of a risk map Explanatory drawing which shows a risk potential along the II line of FIG.

Explanation of symbols

1 ... Vehicle (own vehicle)
2 ... Driving support device 3 ... Stereo camera unit 5 ... Image processing unit (vehicle environment recognition means, vehicle lane estimation means)
6 ... Preview control unit (risk map calculating means, moving position calculating means, risk map correcting means, target route setting means, driving support control determining means)
60 ... Own vehicle driving lane 61 ... Target route Pmax ... Maximum value of risk potential V0 ... Allowable vehicle speed W ... Predetermined width D ... Set distance

Claims (9)

As vehicle environment information, vehicle environment recognition means for recognizing at least an object outside the vehicle,
A risk map calculating means for calculating a two-dimensional risk potential distribution of each object with respect to the vehicle and setting a risk map of the outside environment;
A target route setting means for setting a target route that is a predetermined width that is equal to or greater than a preset vehicle width and that is continuous with a set distance ahead of the vehicle;
A vehicle driving assistance device comprising driving assistance control means for performing vehicle driving assistance control based on the risk potential distribution related to the target route. A moving position calculating means for calculating an estimated moving position after a set time of each object;
The vehicle driving support apparatus according to claim 1, further comprising risk map correction means for correcting a risk potential distribution of each object on the risk map based on the estimated movement position of each object. . A moving speed calculating means for calculating the moving speed of each object;
A relative speed calculation means for calculating a relative speed based on the moving speed and the vehicle speed;
The vehicle driving support apparatus according to claim 1, further comprising a risk map correction unit that corrects a risk potential distribution of each object on the risk map based on the relative speed.   The risk map correcting means forms a risk potential distribution similar to the risk potential distribution at the current position of the object at the estimated movement position, and the risk potential distribution at the current position and the risk potential at the estimated movement position. The vehicle driving support device according to claim 2 or 3, wherein a continuous distribution is set as a final risk potential distribution of the object.   The risk map correcting means reduces the risk potential distribution at the current position by a set gain when the risk potential distribution at the current position and the risk potential distribution at the estimated movement position are continued. The vehicle driving support device according to claim 4. The outside environment recognition means identifies the type of road on which the vehicle is traveling,
The risk map calculating means synthesizes a risk potential of a road set in advance according to the road type to the calculated risk potential distribution of each object, and sets a risk map of the outside environment. The vehicle driving support device according to any one of claims 1 to 5. A vehicle lane estimation unit for estimating the vehicle lane on the road recognized by the outside environment recognition unit;
7. The target route setting means according to claim 1, wherein the target route setting means sets the target route while avoiding a high risk among the risk potential regions distributed in the host vehicle lane. The vehicle driving support device according to Item.   8. The vehicle driving support apparatus according to claim 7, wherein the target route setting means variably sets the set distance according to a type of road on which the host vehicle is traveling.   8. The driving support control means, wherein the vehicle speed allowed for the host vehicle is set such that the higher the maximum risk potential on the target route, the lower the speed, and the lower the vehicle speed, the higher the speed. The vehicle driving support device according to claim 8.

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