VEHICLE TRAVEL CONTROL DEVICE AND VEHICLE TRAVEL CONTROL METHOD

Abstract

A vehicle travel control device (10) for controlling the travel of an own vehicle based on a predicted route which is a future travel route of the own vehicle, the device comprising: an inter-vehicle distance sensor (12) for detecting a distance between vehicles by transmitting and receiving monitoring waves provided to the own vehicle, as an object detecting means for detecting an object; a trajectory calculation means (25) for calculating a moving location of a preceding vehicle traveling ahead of the own vehicle based on the detection result of the inter-vehicle distance sensor (12); a route prediction means (21) for calculating the predicted route based on the moving location of the preceding vehicle calculated by the trajectory calculation means (25); an axial deviation detecting means (32) for detecting the axial deviation of the inter-vehicle distance sensor (12); an invalidation processing means (33) for invalidating the predicted route calculated by the route prediction means (21) when the axial deviation detection means (32) detects that an axial deviation of the inter-vehicle distance sensor (12) occurs; and an alternative prediction means (22) for calculating the predicted route based on the yaw rate of the own vehicle, wherein the invalidation processing means (33) invalidates the predicted route calculated by the route predicting means (21) and validates the predicted route calculated by the alternative predicting means (22) when the axial deviation detecting means (32) detects that an axial deviation of the inter-vehicle distance sensor (12) occurs.

Description

Technical field

[0001] The present invention relates to a vehicle control technology for controlling the travel of an own vehicle based on a predicted route of the own vehicle. State of the art

[0002] Vehicle following control, in which a host vehicle follows a preceding vehicle traveling in the same lane as the host vehicle among the preceding vehicles traveling in front of the host vehicle, is known as an example of vehicle travel support control. It is important that such vehicle following control accurately selects the vehicle traveling in the same lane as the host vehicle among the preceding vehicles detected by a sensor, a camera, and the like. Therefore, conventionally, calculating a future travel route of the host vehicle and setting the preceding vehicle present on the future travel route as the target of the vehicle following control have been performed. Furthermore, various methods for calculating the future travel route of the host vehicle have been proposed (see, for example, JP 2002-531886 A).JP 2002 - 531 886 A discloses that a travel location of the preceding vehicle traveling in front of the own vehicle is stored, and the stored travel location is used to calculate the future travel route of the own vehicle.

[0003] Furthermore, from US 5 964 822 A1 a system is known for automatically measuring and compensating for any angle of misalignment of a forward-facing sensor of a vehicle, wherein the sensor provides data on the yaw or heading angle and the distance to another vehicle in order to estimate the position and line of travel of the other vehicle and thus provide a determined misalignment of the own vehicle to a collision warning system and / or a cruise control system.

[0004] Furthermore, DE 197 51 004 A1 discloses a radar arrangement for a vehicle which is moved relative to its surroundings and which determines a current direction of movement from tracks formed by a plurality of detected vehicles and, if this direction of movement deviates from the orientation of the radar arrangement, the object angle determined is used to correct the deviation and relate it to the direction of movement.

[0005] US 2005 / 0 062 615 A1 also discloses that an object detection device for driver assistance systems in motor vehicles measures data about the location and / or the state of movement of objects in the surroundings of the vehicle and whose detection areas overlap each other, wherein an error detection device checks the measured data for contradictions and outputs an error signal if a contradiction is detected. Summary of the inventionTechnical problem

[0006] Due to the installation conditions of a sensor or similar, there are cases where an axial deviation of the sensor occurs, and it has been detected that the position of objects differs from the actual position. It is thought that under such conditions, the route of the own vehicle is predicted to be in an incorrect direction.

[0007] An object of the present invention is to provide a vehicle travel control technology that can prevent the prediction accuracy of the travel route of a host vehicle from decreasing. This object is achieved by the features of the independent claims. Further embodiments are disclosed in the dependent claims. Solution to the problem

[0008] The present invention uses the following means.

[0009] The present invention relates to a vehicle travel control device for controlling the travel of the own vehicle based on the predicted route, which is the future travel route of the own vehicle. The travel control device of the present invention includes an inter-vehicle distance sensor for detecting a distance between vehicles by transmitting and receiving monitoring waves provided to the own vehicle as an object detection means for detecting an object; a moving trajectory calculation means for calculating a moving location of a preceding vehicle traveling in front of the own vehicle based on the detection result of the inter-vehicle distance sensor; a route prediction means for calculating the predicted route based on the moving location of a preceding vehicle calculated by the moving trajectory calculation means;an axial deviation detection means for detecting the axial deviation of the inter-vehicle distance sensor; and an invalidation processing means for invalidating the predicted route calculated by the route prediction means when the axial deviation detection means detects that an axial deviation of the inter-vehicle distance sensor occurs.

[0010] Under conditions where the axis of the inter-vehicle distance sensor is deviated in the horizontal direction, there is a risk that the preceding vehicle will be incorrectly detected as being present on the right side or the left side, more than it actually is. Taking this point into account, the cruise control device of the present invention invalidates the results of the route prediction of the own vehicle based on the moving location of the preceding vehicle by the above-mentioned configuration when it is determined that an axial deviation of the inter-vehicle distance sensor has occurred. Therefore, the incorrect detection of the preceding vehicle caused by the axial deviation of the inter-vehicle distance sensor can be controlled.The cruise control apparatus of the present invention controls the travel route of the own vehicle from being predicted in the incorrect direction, and appropriate vehicle cruise control can thereby be carried out. Short description of the drawings Fig. 1 is a block diagram illustrating a schematic configuration of the vehicle travel control device. Fig. 2 is a diagram for explaining the calculation method of the predicted route of the own vehicle. Fig. Figure 3 is a diagram illustrating the case of driving at a constant distance between vehicles under the route predictions when an axial deviation occurs. Fig. 4 is a diagram illustrating a state in which the distance between vehicles in the route predictions becomes larger when an axial deviation occurs. Fig. 5 is a diagram illustrating a state in which the distance between vehicles in the route predictions becomes smaller when an axial deviation occurs. Fig. Figure 6 is a table showing the influence due to axial deviation in each of the route prediction methods. Fig. Figure 7 is a flowchart illustrating the process operations of the validation / invalidation determination process. Description of the embodiments

[0011] Below, an embodiment specifying the vehicle travel control device will be explained with reference to the drawings. The travel control device according to the present embodiment is mounted on a vehicle and performs the vehicle following control for traveling following the preceding vehicle traveling in the same lane as the own vehicle among the preceding vehicles traveling in front of the own vehicle. The vehicle following control controls the distance between the own vehicle and the preceding vehicle. First, a schematic configuration of the travel control device of the present embodiment will be explained using Fig. 1 can be explained.

[0012] In Fig. 1, the cruise control device 10 is a computer equipped with a central processing unit (CPU), a random access memory (RAM), a read-only memory (ROM), an input / output (I / O), and the like. The cruise control device 10 includes a route prediction unit 20, an object detection unit 31, an axial deviation determination unit 32, a predicted route setting unit 33, a followed vehicle setting unit 35, and a control target value calculation unit 36. The CPU realizes each of these functions by executing the programs installed in the ROM. An object detection means for detecting an object present in the vehicle periphery is mounted on the vehicle (own vehicle).The cruise control device 10 receives the object detection information from the object detection means and executes vehicle following control with respect to the preceding vehicle based on the input information. The imaging device 11 and the radar device 12 are provided in the host vehicle as the object detection means.

[0013] The imaging device 11 is an on-board camera and is configured by a charge-coupled device (CCD) camera, a complementary metal oxide semiconductor (CMOS) image sensor, a near-infrared camera, and the like. The imaging device 11 captures images of the peripheral environment including the roadway of the own vehicle and produces image data indicative of the captured image to sequentially output it to the cruise control device 10. The imaging device 11 is installed, for example, near the upper side of the front windshield of the own vehicle and captures images of a region extending over a predetermined angular range θ1 in the forward direction of the vehicle from the center of the imaging axis. Note that the imaging device 11 may be a monocular camera or a stereo camera.

[0014] The radar device 12 is a detection device for detecting objects by transmitting electromagnetic waves as transmission waves (monitoring waves) and receiving the reflected waves. In the present embodiment, it is constituted by a millimeter-wave radar. The radar device 12 is mounted on the front of the vehicle, and the radar signal scans the area extending over a predetermined angular range θ2 (θ2 < θ1) in the forward direction of the vehicle from the optical axis center. Further, the radar device 12 generates the distance measurement data based on the time until the reflected wave is received after transmitting the electromagnetic waves in the forward direction of the vehicle, and sequentially outputs the generated distance measurement data to the cruise control device 10.The distance measurement data includes information regarding the direction in which the object exists, the distance to the object, and the relative speed. The radar device 12 corresponds to an inter-vehicle distance sensor.

[0015] Note that when the vehicle is transported, the imaging device 11 and the radar device 12 are each mounted so that the imaging axis, which is the reference axis of the imaging device 11, and the optical axis, which is the reference axis of the radar device 12, are in the same direction as the direction parallel to the road surface of the own vehicle. The detectable range of the imaging device 11 and the detectable range of the radar device 12 overlap each other in at least a part.

[0016] The cruise control device 10 receives the image data from the imaging device 11 and the distance measurement data from the radar device 12, and receives the detection signals from each sensor provided in the vehicle, respectively. A yaw rate sensor 13 for detecting the angular velocity (hereinafter referred to as the "yaw rate") in the turning direction of the vehicle, a speed sensor 14, and the like for detecting the speed are provided as the respective types of sensors. Further, a steering angle sensor 15 for detecting the steering angle, an ACC switch 16 to be operated when a driver selects the vehicle following control mode, and the like are provided.

[0017] The route prediction unit 20 is a calculation unit for predicting the travel route of the own vehicle and is provided with a first predicted route calculation unit 21 and a second predicted route calculation unit 22. Among the plurality of route prediction means, the first predicted route calculation unit 21 calculates the future travel route of the own vehicle based on the moving position of the preceding vehicle traveling in front of the own vehicle. Further, the second predicted route calculation unit 22 calculates the future travel route of the own vehicle based on the yaw rate of the own vehicle.

[0018] In detail, the first predicted route calculation unit 21 receives the stationary object information from the stationary object information acquisition unit 23, the white line information from a white line information acquisition unit 24, and the other vehicle's moving location information from an other vehicle's moving location acquisition unit 25, respectively. The first predicted route RA, which is the predicted route of the own vehicle, is calculated by combining the input information. Note that the own vehicle's route prediction, which is independent of the own vehicle's yaw rate, is possible with the first predicted route calculation unit 21.

[0019] The stationary object information acquisition unit 23 calculates the position information regarding the stationary roadside objects (e.g., guardrails, walls, and the like) present along the road on which the host vehicle is traveling based on the distance measurement data from the radar device 12 and outputs the calculated position information to the first predicted route calculation unit 21 as the stationary object information. The white line information acquisition unit 24 calculates the information regarding the road section lines (white lines) included in the images captured by the imaging device 11 based on the image data from the imaging device 11 and outputs the calculated information as the white line information to the first predicted route calculation unit 21.Specifically, the white line information calculation method extracts, for example, the edge points considered to be white line candidates from the image data based on the change rate, etc., of the luminance in the horizontal direction of the image. Further, the extracted edge points are sequentially stored in one frame, and the white line information is calculated based on the stored history of the white line edge points.

[0020] The other-vehicle moving location acquisition unit 25 calculates the position of the preceding vehicle, which is a coordinate pair representing the passing point of the preceding vehicles, in a predetermined cycle based on the distance measurement data (the distance information and the horizontal position information of the own vehicle and the preceding vehicle) from the radar device 12, and stores the calculated preceding vehicle position in a time series. Further, the moving location of the preceding vehicle is calculated based on the time series data of the stored preceding vehicle position, and the calculated moving location is output to the first predicted route calculation unit 21 as the other-vehicle moving location information.Note that the other-vehicle moving location acquisition unit 25 calculates the moving location information not only for the vehicles traveling in the same lane as the own vehicle among the preceding vehicles, but also for the vehicles traveling in the lane adjacent to the own vehicle, and this calculation is used in the route prediction of the own vehicle. The other-vehicle moving location acquisition unit 25 corresponds to a trajectory calculation means.

[0021] Fig. 2 shows an illustration of the processes for calculating the first predicted route RA in the first predicted route calculation unit 21. In Fig. 2. (a) represents a plurality of stationary object detection points Pa, which is the result of the three-dimensional object (for example, a guardrail) being detected as the stationary roadside object by the radar device 12. Further, (b) represents the white line information Pb, which is the result of the white lines being detected by the imaging device 11. Further, (c) represents the history of the plurality of vehicle detection points Pc, which is the result of the preceding vehicle M2 being detected by the radar device 12. Note that Fig. 2(c) represents a vehicle traveling in the same lane as the own vehicle M1 and a vehicle traveling in the lane adjacent to the own vehicle M1 as the preceding vehicle M2. Furthermore, in Fig. 2, (d) represents the first predicted route RA obtained from the calculation using the stationary object detection points Pa, the white line information Pb, and the vehicle detection point Pc. Note that the preceding vehicle position may be the vehicle detection point Pc or the value averaging the vehicle detection points Pc for the predetermined sections.

[0022] The first predicted route calculation unit 21 first compares the moving location of the preceding vehicle M2 calculated from the vehicle detection point Pc with the white lines and the stationary roadside objects, and excludes (invalidates) the moving location of the preceding vehicle M2 that does not conform to the white lines and the shape of the stationary roadside objects. Next, if there is only one non-excluded moving location of the preceding vehicle M2, the first predicted route RA is calculated using the moving location to calculate a weighted average of the moving location of the preceding vehicle M2 and the white line information Pb.Further, when there are a plurality of the non-excluded moving locations of the preceding vehicle M2, the first predicted route RA is calculated by using a moving location that is the average of the moving location to calculate a weighted average of the moving location of the preceding vehicle M2 and the white line information Pb.

[0023] The second predicted route calculation unit 22 receives the turning radius (hereinafter referred to as the "estimated value R") of the roadway of the own vehicle M1 from the turning radius estimation unit 26, and the inputted estimated value R is used to calculate the second predicted route RB, which is a predicted route of the own vehicle M1. The turning radius estimation unit 26 calculates the estimated value R from the yaw angle detected by the yaw rate sensor 13 and the speed detected by the speed sensor 14. The calculation method of an estimated value R is not limited to this, and the estimated value R may be calculated, for example, using the image data, or may be calculated from the steering angle detected by the steering angle sensor 15 and the speed detected by the speed sensor 14.Note that the first predicted route calculation unit 21 corresponds to a “route prediction means”, the second predicted route calculation unit 22 corresponds to an “alternative prediction means”, and the first predicted route calculation unit 21 and the second predicted route calculation unit 22 correspond to the “plurality of route calculation means”.

[0024] The predicted route setting unit 33 sets the course of the own vehicle M1 predicted by a route predicting means among the plurality of route predicting means. The predicted route setting unit 33 selects one of the first predicted route RA calculated by the first predicted route calculating unit 21 and the second predicted route RB calculated by the second predicted route calculating unit 22, and sets the selected predicted route as the predicted route to be used in the vehicle following control. The followed vehicle setting unit 35 uses the predicted routes inputted by the predicted route setting unit 33 and sets the preceding vehicle M2, which is present among the preceding vehicles M2 traveling in the forward direction of the own vehicle M1 on the predicted route, as the followed vehicle.The predicted route setting unit 33 corresponds to an invalidation processing means.

[0025] The control target value calculation unit 36 calculates a control target value for maintaining the distance between the followed vehicle and the host vehicle M1, which has been set by the followed-vehicle setting unit 35, by controlling the traveling speed of the host vehicle M1. Note that in this case, the control target value calculation unit 36 calculates the control target value for maintaining the distance between vehicles at a preset target interval. Specifically, the target output of an in-vehicle internal combustion engine, the required braking power, etc., are calculated, and these values are output to the electronic control unit of the internal combustion engine (engine ECU 41).In the present embodiment, the cruise control device 10 outputs a control signal to the engine ECU 41 and outputs a control signal from the engine ECU 41 to the brake electronic control unit (brake ECU 42). Note that, in terms of configuration, the cruise control device 10 may output a control signal to each of the engine ECU 41 and the brake ECU 42.

[0026] Regarding the route prediction of the own vehicle M1, the present embodiment uses the route prediction result calculated by the first predicted route calculation unit 21, that is, the route prediction result based on the moving location of the preceding vehicle M2, to select the following vehicle. The reasons for this are as follows. When traveling on a straight road, the first predicted route RA, which is the route prediction result based on the moving location of the preceding vehicle M2, and the second predicted route RB, which is the route prediction result based on the estimated value R, hardly change at all.However, when the followed vehicle enters a curve and, on the other hand, the second predicted route RB is used to select the followed vehicle when the host vehicle M1 has been traveling on a straight road before approaching a curve, there is a risk that the preceding vehicle M2 is not in the same lane as the host vehicle M1, and the preceding vehicle M2 existing in the adjacent lane is mistakenly selected as the followed vehicle. Therefore, the present embodiment specifically uses the first predicted route RA to select the followed vehicle.

[0027] Returning to the statement of Fig. 1, the object detection unit 31 receives the image data from the imaging device 11 and the distance measurement data from the radar device 12, and uses the input data to detect an object present near the vehicle. The object detection unit 31 performs fusion between the image data and the distance measurement data regarding the target when the target is included in the image data and the target detected by the radar device 12 are targets belonging to the same object. As an example of the data fusion method, a plurality of detection points existing within the range of the predetermined fusion are fused as the data belonging to the same object with respect to the respective image data and distance measurement data.Further, when the target detected by the imaging device 11 and the target detected by the radar device 12 are in a predetermined positional relationship, the targets are considered to be data belonging to the same object, and the data are fused.

[0028] The axial deviation detection unit 32 detects whether or not a deviation (hereinafter referred to as the "axial deviation") has occurred in the optical axis of the radar device 12. The detection of the axial deviation can be performed according to a well-known method. For example, the axial deviation of the radar device 12 is detected based on a vanishing point calculated using the image data and the transmission direction of the radar. Alternatively, an axial deviation of the radar device 12 is detected based on the stationary object detected by the radar device 12 and the estimated value R. The axial deviation detection unit 32 outputs a signal indicating the detection result to the predicted route setting unit 33. The axial deviation detection unit 32 corresponds to axial deviation detection means.

[0029] Under conditions where the axis of the radar device 12 is deviated in the horizontal direction, the preceding vehicle M2 is incorrectly detected as being present on the right side or the left side, more than it actually is. In this case, the course of the preceding vehicle M2 is calculated in the incorrect direction; thus, the route prediction of the host vehicle M1 cannot be performed with high accuracy.

[0030] Fig. 3 to Fig. 5 are diagrams for explaining the route prediction of the own vehicle M1 in the case where the axial deviation of the radar device 12 occurs. Fig. 3 to Fig. 5 assumes the case where the axial deviation with respect to the front surface (travel direction) of the host vehicle M1 to the left side occurs in a state in which the host vehicle M1 and the preceding vehicle M2 are arranged in front of and behind each other and travel in the same lane of a straight road. Illustrated by Fig. 3 illustrates the case where the host vehicle M1 and the preceding vehicle M2 are traveling and the distance between the vehicles is constant (when the distance between vehicles is constant). Fig. 4 illustrates the case when the distance between vehicles gradually increases (when separating from the preceding vehicle M2) by separating the preceding vehicle M2 from the own vehicle M1. Fig. 5 the case where the distance between vehicles gradually decreases (when approaching the preceding vehicle M2) by the own vehicle M1 following the preceding vehicle M2.

[0031] The stationary object detection point Pa, which detects the steering plank, which is a three-dimensional object provided on the roadside, by means of the radar device 12, is in Fig. 3 to Fig. 5. The stationary object detection points Pa appear at the position where the separation distance in the lateral direction from the own vehicle M1 is large in the area close to the own vehicle M1 and at the position where the separation distance in the lateral direction is small in the area far from the own vehicle M1 in the traveling direction of the own vehicle M1 due to the axial deviation to the left side of the radar device 12. In this case, the guardrail is detected to be inclined to the right side with respect to the own vehicle M1. Note that the preceding vehicle position and the vehicle detection point Pc are explained in the same way in the explanation below.

[0032] Further, when the axial deviation to the left side has occurred by the radar device 12, it is recognized that the preceding vehicle M2 exists in a position offset to the right side relative to the host vehicle M1. In short, it is recognized that the preceding vehicle M2 exists only by the offset amount α more to the right side than the actual position. Furthermore, the influence of the axial deviation of the radar device 12 becomes greater the farther the distance from the radar device 12 is. When the distance between the host vehicle M1 and the preceding vehicle M2 is constant as in Fig. 3, the offset quantity α is therefore constant. In this case, as in Fig. As shown in Figure 3, the traveling position of the preceding vehicle M2 is the same as the actual traveling direction. Therefore, the first predicted route RA of the own vehicle M1, calculated from the time series data of the preceding vehicle position Pc, is the correct route.

[0033] On the other hand, in a state where the preceding vehicle M2 gradually separates from the own vehicle M1 and the distance between the own vehicle M1 and the preceding vehicle M2 gradually increases, as the distance between vehicles increases, the displacement amount α gradually increases. Therefore, as shown in Fig. 4, the offset amount α to the right side with respect to the time series data of the preceding vehicle position Pc is larger, the newer the acquisition period of the data is (in Fig. 4 the position data further away from the own vehicle M1). In this case, even if the preceding vehicle M2 is traveling straight along the shape of the road, due to the influence of the axial deviation of the radar device 12, it is detected that the preceding vehicle M2 is moving to the right side, as shown in Fig. 4. Therefore, the first predicted route RA of the own vehicle M1 calculated from the time series data of the preceding vehicle position Pc turns to the right, as shown in Fig. 4 shown.

[0034] The first predicted route RA is set to the right in a state in which the distance between the own vehicle M1 and the preceding vehicle M2 gradually increases; thus, as shown in Fig. 4, the predicted deviation amount β generated by the route prediction during an axial deviation is generated to the right side of the preceding vehicle M2. Therefore, when the first predicted route RA is used to execute the cruise control, it acts to make the detection error (offset amount α) of the position in the lateral direction of the preceding vehicle M2 caused by the axial deviation of the radar device 12 smaller. In short, when the first predicted route RA to the right was used to execute the cruise control, the predicted route will be erroneous on the side mitigating the influence of the axial deviation. Note that the relationship (α > β) in which the offset amount α is larger than the predicted deviation amount β is maintained in the state where the preceding vehicle M2 is traveling in the forward direction of the host vehicle M1.

[0035] In a state where the host vehicle M1 gradually gets closer to the preceding vehicle M2, and the distance between the host vehicle M1 and the preceding vehicle M2 gradually decreases as the distance between vehicles decreases, the offset amount α gradually decreases. Therefore, as shown in Fig. 5, the offset amount α to the right side with respect to the time series data of the preceding vehicle position Pc is smaller, the newer the acquisition period of the data is (in Fig. 5 the position data further away from the own vehicle M1). In this case, although the preceding vehicle M2 is traveling straight along the shape of the road, due to the influence of the axial deviation of the radar device 12, it is detected as if the preceding vehicle M2 is moving to the left side, as in Fig. 5. Therefore, the first predicted route RA of the own vehicle M1, which is calculated from the time series data of the preceding vehicle position Pc, turns to the left as shown in Fig. 5 shown.

[0036] The first predicted route RA is set to the left in a state in which the distance between the own vehicle M1 and the preceding vehicle M2 gradually becomes smaller; thus, as shown in Fig. 5, the predicted deviation amount β is generated on the left side of the preceding vehicle M2. Therefore, when the first predicted route RA was used to execute cruise control, in addition to the detection error (offset amount α) of the position in the lateral direction of the preceding vehicle M2 caused by axial deviation of the radar device 12, a deviation part of the predicted deviation amount β is generated.

[0037] Taking these points into consideration, the present embodiment, when it is detected that an axial deviation of the radar device 12 has occurred, invalidates the first predicted route RA of the host vehicle M1 calculated based on the moving location of the preceding vehicle M2 and prohibits the use of the first predicted route RA. Further, when the first predicted route RA is invalidated, the vehicle following control of the vehicle is executed by validating the second predicted route RB of the host vehicle M1 predicted based on the estimated value R and using the second predicted route RB instead of the first predicted route RA.

[0038] Fig. 6 is a table illustrating the route prediction methods of the own vehicle M1 with respect to the influence due to the axial deviation of the radar device 12. When the prediction method based on the moving location of the preceding vehicle M2 is used, the amount of deviation (detection error) between the position in the lateral direction of the preceding vehicle M2 detected by the radar device 12 and the position in the lateral direction of the preceding vehicle M2 based on the route prediction is α when the distance between the own vehicle M1 and the preceding vehicle M2 is constant. Further, the deviation "α-β" is generated in the state where the distance between vehicles gradually increases. Furthermore, a large deviation of "α+β" is generated in the state where the distance between vehicles gradually decreases, and the influence of the axial deviation is increased.On the other hand, the influence of the axial deviation can be minimized by switching to the prediction method based on the estimated value R in a state where the distance between vehicles gradually becomes smaller.

[0039] Note that when switching to the prediction method based on the moving location of the preceding vehicle M2 in a state in which the distance between the own vehicle M1 and the preceding vehicle M2 gradually increases, the amount of deviation between the position in the lateral direction of the preceding vehicle M2 detected by the radar device 12 and the position in the lateral direction of the preceding vehicle M2 due to the route prediction increases from “α-β” to “α” (see Fig. 6). However, the present embodiment prioritizes reducing the influence of the axial deviation in a state where the distance between vehicles gradually becomes smaller.

[0040] When the imaging device 11 captures an image of the preceding vehicle M2 so that the position in the lateral direction of the preceding vehicle M2 can be accurately recognized by the imaging device 11, it is possible for the offset amount α to be made zero. Therefore, even if the prediction method based on the moving location of the preceding vehicle M2 was used in a state where the distance between the host vehicle M1 and the preceding vehicle M2 gradually becomes smaller, the influence on the position in the lateral direction of the preceding vehicle M2 caused by the axial deviation decreases. In this case, as shown in Fig. 6, in the state where the distance between vehicles gradually becomes smaller, the deviation between the position in the lateral direction of the preceding vehicle M2 detected by the radar device 12 and the position in the lateral direction of the preceding vehicle M2 based on the route prediction is stored as “β”.

[0041] Therefore, the present embodiment determines whether or not the target deemed to be the same object as the preceding vehicle M2 detected by the radar device 12 is included in the image data acquired by the imaging device 11. Further, when the image data includes the target deemed to be the same object as the preceding vehicle M2, even if the axial deviation of the radar device 12 occurred, the first predicted route RA of the own vehicle M1 calculated based on the moving location of the preceding vehicle M2 is validated, and the first predicted route RA is used to execute the vehicle following control.

[0042] Next, the validation / invalidation determination process of the route prediction, which is executed by the predicted route setting unit 33, is carried out using Fig. 7. This process is executed every predetermined period during vehicle travel by the ECU of the cruise control device 10 and when the ACC switch 16 is in an on state.

[0043] As in Fig. As shown in Fig. 7, the cruise control device 10 determines whether or not the axial deviation of the radar device 12 that has occurred is detected based on a determination signal input from the axial deviation determination unit 32 in step S101. As a result, if it is determined that an occurrence of axial deviation has not been detected (when S101 is NO), the cruise control device 10 proceeds to the process of step S104. Further, the cruise control device 10 validates the first predicted route RA as the future travel route of the host vehicle M1 in step S104.

[0044] However, the cruise control device 10 proceeds to the process of step S102 if the axial deviation determining unit 32 determines that an axial deviation is detected (when S101 is YES). Further, in step S102, the cruise control device 10 determines whether or not the target deemed to be the same as the preceding vehicle M2 (target corresponding to the preceding vehicle M2) detected by the radar device 12 is included in the target included in the image data acquired by the imaging device 11. Note that the process makes an affirmative decision in the case where there is a target that can perform the data fusion between the target included in the image data and the target detected by the radar device 12.

[0045] As a result, if it is determined that the target considered to be the same object as the preceding vehicle M2 is included in the target included in the image data (when S102 is YES), the cruise control device 10 proceeds to the process of step S104 and sets the first predicted route RA as the predicted route used in the vehicle following control. However, if it is determined that the target considered to be the same object as the preceding vehicle M2 is not included in the target included in the image data (when S102 is NO), the cruise control device 10 proceeds to the process of step S103. Further, in step S103, the cruise control device 10 invalidates the first predicted route RA and validates the second predicted route RB as the predicted route used in the vehicle following control.Therefore, the cruise control device 10 has a target detecting means.

[0046] The above-mentioned present embodiment can achieve the following excellent result.

[0047] The cruise control device 10 according to the present embodiment is configured such that, when it is determined that an axial deviation of the radar device 12 has occurred, the result of the first predicted route RA of the host vehicle M1 based on the moving location of the preceding vehicle M2 is invalidated. Under conditions where the axis of the radar device 12 has deviated in the horizontal direction, there is a risk of making an incorrect detection if the preceding vehicle M2 is more present on the right side or the left side than it actually is. Taking this point into account, the cruise control device 10 according to the present embodiment can control the incorrect detection of the preceding vehicle M2 caused by the axial deviation of the radar device 12 by the above-mentioned configuration.The cruise control device 10 according to the present embodiment controls the travel route of the own vehicle M1 by not being predicted in the incorrect direction, and as a result, appropriate vehicle cruise control can be performed.

[0048] The cruise control device 10 according to the present embodiment is configured such that the first predicted route RA of the host vehicle M1 is validated when the image data acquired by the imaging device 11 includes the target deemed to be the same object as the preceding vehicle M2 detected by the radar device 12, even if it is detected that an axial deviation has occurred. The cruise control device 10 according to the present embodiment thereby recognizes the target belonging to the same object through both the imaging device 11 and the radar device 12, and thus, when the image data can be used to calculate the precise position of the preceding vehicle M2, the influence of the object detection error caused by the axial deviation can be eliminated.Furthermore, the predicted deviation in the route prediction of the own vehicle M1 can be minimized.

[0049] The cruise control device 10 according to the present embodiment is configured such that, when the first predicted route RA of the host vehicle M1 is invalidated accompanying the detection that the axial deviation has occurred by the radar device 12, the second predicted route RB of the host vehicle M1 is instead validated, and the second predicted route RB is used to execute the vehicle following control. The cruise control device 10 according to the present embodiment can thereby continuously execute the vehicle following control and can execute the control according to the driver's needs. (Other embodiments)

[0050] The present invention is not limited to the above-mentioned embodiment and can be embodied, for example, as follows.

[0051] The above embodiment is configured such that the first predicted route calculation unit 21 receives the stationary object information, the white line information, and the moving location information of the other vehicle, and uses this input information to calculate the first predicted route RA of the host vehicle M1. The method for calculating the first predicted route RA is not limited to this, and the first predicted route RA may be calculated using only the moving location information of the other vehicle, for example. Further, the first predicted route RA may be calculated from the moving location information of the other vehicle and the stationary object information, and the first predicted route RA may be calculated from the moving location information of the other vehicle and the white line information.

[0052] The above-mentioned embodiment is configured such that, when it is detected that an axial deviation of the radar device 12 has occurred, the first predicted route RA of the host vehicle M1 is invalidated and the second predicted route RB is validated, but the present invention is not limited to this. For example, when it is detected that an axial deviation of the radar device 12 has occurred, the route prediction of the host vehicle M1 itself may be invalidated. In short, when it is detected that an axial deviation of the radar device 12 has occurred, the control using the route prediction result of the host vehicle M1 can be prohibited.

[0053] When it has been detected that the axial deviation of the radar device 12 has occurred, whether the first predicted route RA of the host vehicle M1 is validated or invalidated can be selected depending on the distance between the host vehicle M1 and the preceding vehicle M2. Specifically, in the case where the first determination means is provided for determining whether the distance between vehicles is constant or not, and it has been detected that an axial deviation has occurred, the first predicted route RA can be validated if the first determination means determines that the distance between the vehicles is constant. Regarding this embodiment, as shown in Fig. 3 explains that the route prediction of the first predicted route RA is not wrong when the distance between vehicles is constant, thus the prediction accuracy is ensured.

[0054] In the case where the second determination means is provided to determine whether or not the distance between the own vehicle M1 and the preceding vehicle M2 is in a state that has become large, and it has been detected that an axial deviation has occurred, the first predicted route RA of the own vehicle M1 can be validated if the second determination means determines that the distance between vehicles is in a state that has become large. This embodiment calculates, as in Fig. 4 explains the first predicted route RA on the side which mitigates the influence of the axial deviation when the preceding vehicle M2 moves to the side which is to be replaced by the own vehicle M1.

[0055] The configuration for invalidating the first predicted route RA of the own vehicle M1 accompanying the generation of an axial deviation is not limited to the configuration that prohibits the use of the first predicted route RA. The configuration for invalidating the first predicted route RA of the own vehicle M1 may, for example, be a configuration for deleting the data of the calculated first predicted route RA. Further, it may be a configuration that prohibits the calculation process of the first predicted route RA, and it may be a configuration that deletes or prohibits the use of the moving location of the preceding vehicle M2.

[0056] The above-mentioned embodiment is configured such that, when the image data includes the target deemed to be the same object as the preceding vehicle M2 detected by the radar device 12, the first predicted route RA of the host vehicle M1 calculated based on the moving location of the preceding vehicle M2 is validated even if the axial deviation of the radar device 12 occurred, and the first predicted route RA is used to execute the vehicle following control, but the present invention is not limited to this. The vehicle following control method in this case, taking into account the predicted deviation due to the axial deviation, may, for example, invalidate the first predicted route RA. As shown in Fig.As shown in Figure 6, the vehicle following control method makes it possible to have no influence due to the axial deviation by using the predicted route based on the estimated value R and the image data when driving straight.

[0057] The above-mentioned embodiment is constituted by the imaging device 11 and the radar device 12 as the object detection means, but it is not limited thereto, and can be used, for example, in a configuration that uses ultrasound at a transmission source to provide sonar for detecting an object. Furthermore, the technology of the present invention can be used in a vehicle in which an imaging device 11 is not mounted.

[0058] The above-mentioned embodiment was explained with respect to the case where it is used in vehicle following control for traveling following the preceding vehicle M2 traveling in the same lane as the host vehicle M1. The technology of the present invention can be applied to the route prediction of the host vehicle M1 to avoid a collision between the host vehicle M1 and the other vehicle. Note that the present invention can be implemented in various forms, such as a program for executing each functional unit (means) constituting the above-mentioned cruise control device 10 in a computer and a medium storing the program, and further a vehicle cruise control method. List of reference symbols

[0059] 10...Cruise control device, 11...Imaging device, 12...Radar device, 13...Yaw rate sensor, 20...Route prediction unit, 21...First predicted route calculation unit, 22...Second predicted route calculation unit, 23...Stationary object information acquisition unit, 24...White line information acquisition unit, 25...Other vehicle moving location acquisition unit, 26...Curve radius estimation unit, 31...Object detection unit, 32...Axial deviation determination unit, 33...Predicted route setting unit, 35...Followed vehicle setting unit, 36...Control target value calculation unit, 41...Engine ECU, 42...Brake ECU

Claims

[1] A vehicle travel control device (10) for controlling the travel of an own vehicle on the basis of a predicted route which is a future travel route of the own vehicle, the device comprising: an inter-vehicle distance sensor (12) for detecting a distance between vehicles by transmitting and receiving monitoring waves provided to the own vehicle, as an object detecting means for detecting an object; a trajectory calculation means (25) for calculating a moving location of a preceding vehicle traveling ahead of the own vehicle based on the detection result of the inter-vehicle distance sensor (12); a route prediction means (21) for calculating the predicted route based on the moving location of the preceding vehicle calculated by the trajectory calculation means (25); an axial deviation detecting means (32) for detecting the axial deviation of the inter-vehicle distance sensor (12); an invalidation processing means (33) for invalidating the predicted route calculated by the route prediction means (21) when the axial deviation detection means (32) detects that an axial deviation of the inter-vehicle distance sensor (12) occurs; and an alternative prediction means (22) for calculating the predicted route based on the yaw rate of the own vehicle, wherein the invalidation processing means (33) invalidates the predicted route calculated by the route predicting means (21) and validates the predicted route calculated by the alternative predicting means (22) when the axial deviation detecting means (32) detects that an axial deviation of the inter-vehicle distance sensor (12) occurs. [2] Vehicle travel control device (10) according to claim 1, further comprising: an imaging device (11) for capturing images of the peripheral environment including the roadway, which is provided in the own vehicle as the object detection means; and a target detecting means (31) for detecting whether or not a target which is considered to be the same object as the preceding vehicle detected by the inter-vehicle distance sensor (12) is included in the image data acquired by the imaging device (11), wherein the invalidation processing means (33) invalidates the predicted route calculated by the route predicting means (21) when the destination determining means (31) does not determine that the destination is included in the case where it was detected that an axial deviation of the inter-vehicle distance sensor (12) occurs due to the axial deviation detecting means (32), and validates the predicted route calculated by the route predicting means (21) when it is determined that the destination is included. [3] The vehicle travel control device (10) according to claim 1 or 2, further comprising first determining means (20) for determining whether the distance between the host vehicle and the preceding vehicle is constant or not, wherein the invalidation processing means (33) selects whether to validate or invalidate the predicted route calculated by the route prediction in accordance with a determination result of the first determining means (20). [4] The vehicle travel control device (10) according to any one of claims 1 to 3 and 5, further comprising second determination means (20) that determines whether or not the distance between the own vehicle and the preceding vehicle is in a state that has become large, wherein the invalidation processing means (33) selects whether to validate or invalidate the predicted route calculated by the route prediction in accordance with a determination result of the second determination means (20). [5] A vehicle travel control method for controlling the travel of an own vehicle on the basis of a predicted route which is a future travel route of the own vehicle, wherein an inter-vehicle distance sensor (12) for detecting a distance between vehicles by transmitting and receiving monitoring waves is provided as an object detecting means for detecting an object in the own vehicle, the method comprising: a trajectory calculation step (25) for calculating a moving location of a preceding vehicle traveling ahead of the own vehicle based on the detection result of the inter-vehicle distance sensor (12); a route prediction step (21) for calculating the predicted route based on the moving location of the preceding vehicle calculated in the trajectory calculation step (25); an axial deviation detection step (32) for detecting the axial deviation of the inter-vehicle distance sensor (12); an invalidation processing step (33) for invalidating the predicted route calculated by the route prediction step (21) when the axial deviation detection step (32) detects that an axial deviation of the inter-vehicle distance sensor (12) occurs; and an alternative prediction step (22) for calculating the predicted route based on the yaw rate of the own vehicle, wherein the invalidation processing step (33) invalidates the predicted route calculated by the route prediction step (21) and validates the predicted route calculated by the alternative prediction step (22) when the axial deviation detection step (32) detects that an axial deviation of the inter-vehicle distance sensor (12) occurs.

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