WO2020053612A1

WO2020053612A1 - Vehicle behavior prediction method and vehicle behavior prediction device

Info

Publication number: WO2020053612A1
Application number: PCT/IB2018/001121
Authority: WO
Inventors: 安宅佑樹; 南里卓也
Original assignee: 日産自動車株式会社; ルノーエス．ア．エス．
Priority date: 2018-09-13
Filing date: 2018-09-13
Publication date: 2020-03-19
Also published as: JP7143893B2; JPWO2020053612A1

Abstract

In this vehicle behavior prediction method and vehicle behavior prediction device: objects outside the host vehicle are detected; an intersecting vehicle having a planned travel path intersecting with the planned travel path of the host vehicle is identified from the detected objects; a preceding vehicle travelling along the planned travel path of the host vehicle is identified; and the entry of the intersecting vehicle into the planned travel path of the host vehicle is predicted, on the basis of an indicator value representing the distance of a section between the preceding vehicle and the host vehicle, and a first threshold value set on the basis of a change in behavior of the preceding vehicle.

Description

Vehicle behavior prediction method and vehicle behavior prediction device

The present invention relates to a vehicle behavior prediction method and a vehicle behavior prediction device.

Patent Document 1 discloses that a distance between an own vehicle and an on-right-turning vehicle, an own-vehicle speed, and a headway time with a preceding vehicle are obtained from a sensing device, and the distance between the own vehicle and the on-right-turning vehicle is divided by the own vehicle speed. There is proposed a driving support device that compares the vehicle speed with the preceding vehicle by doubling the headway time, reduces the speed according to the criterion, and applies a sudden brake when the right-turning vehicle actually turns right.

JP 2001-52297 A

However, the technology described in Patent Literature 1 has a configuration in which the right turn timing of an oncoming right turn vehicle is determined only from the distance between the host vehicle and the right turn vehicle, the host vehicle speed, and the headway time of the preceding vehicle. For this reason, the behavior of the oncoming right-turn vehicle that changes due to the change in the behavior of the preceding vehicle is not reflected in the determination, and there is a possibility that the deceleration of the host vehicle is delayed.

The present invention has been made in view of the above-described problem, and an object of the present invention is to change the behavior of an intersecting vehicle having a scheduled travel route that intersects the scheduled travel route of the own vehicle due to a change in the behavior of a preceding vehicle. Even in such a case, it is an object of the present invention to provide a vehicle behavior prediction method and a vehicle behavior prediction device capable of predicting the behavior of an intersecting vehicle.

In order to solve the above-described problem, a vehicle behavior prediction method and a vehicle behavior prediction device according to one embodiment of the present invention detect an object outside a host vehicle and, based on the detected object, intersect with a planned traveling route of the host vehicle. Identifying a crossing vehicle having a planned traveling route, identifying a preceding vehicle traveling on the planned traveling route of the own vehicle, an index value indicating a distance between the preceding vehicle and the section between the own vehicle, and a behavior of the preceding vehicle Based on the first threshold value set based on the change, the approach of the crossing vehicle to the planned traveling route of the own vehicle is predicted.

According to the present invention, even when the behavior of an intersecting vehicle having a scheduled traveling route that intersects with the scheduled traveling route of the host vehicle changes due to a change in behavior of a preceding vehicle, the behavior of the intersecting vehicle can be predicted. .

FIG. 1 is a block diagram showing a configuration of a vehicle behavior prediction device according to one embodiment of the present invention. FIG. 2 is a flowchart showing a processing procedure of vehicle behavior prediction according to one embodiment of the present invention. FIG. 3 is a graph showing the relationship between the index value and the entry probability. FIG. 4 is a plan view showing a first traveling scene. FIG. 5 is a plan view showing a second traveling scene. FIG. 6 is a plan view showing a third traveling scene.

Next, an embodiment of the present invention will be described in detail with reference to the drawings. In the description, the same components will be denoted by the same reference symbols, without redundant description.

[Configuration of vehicle behavior prediction device]
The configuration of the vehicle behavior prediction device will be described with reference to FIG. The vehicle behavior prediction device includes an object detection unit 21, a vehicle position estimation unit 23, a map information acquisition unit 25, and a processing unit 100 (controller).

The vehicle behavior prediction device may be applied to a vehicle having an automatic driving function, or may be applied to a vehicle having no automatic driving function. Further, the vehicle behavior prediction device may be applied to a vehicle that can switch between automatic driving and manual driving.

自動 Note that the automatic driving in the present embodiment refers to a state in which at least one of the actuators such as a brake, an accelerator, and a steering is controlled without an occupant's operation. Therefore, other actuators may be operated by the occupant. In addition, the automatic driving may be in a state in which any control such as acceleration / deceleration control and lateral position control is being executed. The manual operation in the present embodiment indicates, for example, a state in which the occupant operates the brake, the accelerator, and the steering.

The object detection unit 21 includes an object detection sensor such as a laser radar, a millimeter-wave radar, and a camera mounted on the own vehicle. The object detection unit 21 detects an object outside the vehicle using a plurality of object detection sensors. Further, the object detection unit 21 detects an object in front of or on the side of the own vehicle. The object detection unit 21 detects moving objects including other vehicles, motorcycles, bicycles, and pedestrians, and stationary objects including parked vehicles and buildings. For example, the object detection unit 21 detects the position, posture (yaw angle), size, speed, acceleration, jerk, deceleration, and yaw rate of the moving object and the stationary object with respect to the own vehicle. The position, posture (yaw angle), size, speed, acceleration, deceleration, and yaw rate of the object are collectively referred to as “behavior” of the object.

The host vehicle position estimating unit 23 includes a position detection sensor mounted on the host vehicle for measuring an absolute position of the host vehicle such as a GPS (Global Positioning System) and odometry. The own-vehicle position estimating device 2 measures the absolute position of the own vehicle, that is, the position, the vehicle speed, the acceleration, the steering angle, and the attitude of the own vehicle with respect to a predetermined reference point, using the position detection sensor. The host vehicle position estimating unit 23 includes an inertial navigation system (Inertial Navigation System, INS), a sensor provided on a brake pedal or an accelerator pedal, a sensor for acquiring vehicle behavior such as a wheel side sensor or a yaw rate sensor, or a laser. A radar, a camera, and the like may be included.

The map information acquisition unit 25 acquires map information indicating the structure of the road on which the vehicle runs. The map information acquired by the map information acquisition unit 25 includes information on the road structure such as the absolute position of the lane, the connection relationship of the lane, and the relative positional relationship. The map information acquired by the map information acquisition unit 25 includes facility information such as a parking lot and a gas station. In addition, the map information includes the position information of the traffic light, the type of the traffic light, and the like. The map information acquisition unit 25 may own a map database storing map information, or may acquire map information from an external map data server by cloud computing. Further, the map information acquisition unit 25 may acquire the map information using vehicle-to-vehicle communication or road-to-vehicle communication.

Alternatively, the map information acquisition unit 25 may acquire the position of the vehicle from the GPS and detect an intersection ahead of the vehicle from the map information in which the lane information is described. In order to acquire the position of the own vehicle, an inertial navigation device or odometry of the own vehicle may be used instead of the GPS, or they may be used together with the GPS. Note that the road structure may be estimated using a sensor that detects the front such as LiDAR.

The processing unit 100 predicts the operation of another vehicle based on the detection result by the object detection unit 21 and the own vehicle position estimating unit 23 and the information obtained by the map information obtaining unit 25, and calculates the operation of the own vehicle from the operation of the other vehicle. A planned traveling route is generated, and the host vehicle is controlled according to the generated planned traveling route.

The processing unit 100 (an example of a control unit or a controller) is a general-purpose microcomputer including a CPU (Central Processing Unit), a memory, and an input / output unit. In the processing unit 100, a computer program (vehicle behavior prediction program) for functioning as a vehicle behavior prediction device is installed. By executing the computer program, the processing unit 100 functions as a plurality of information processing circuits (41, 43, 45, 50, 70, 80, 90) included in the vehicle behavior prediction device.

Here, an example is shown in which a plurality of information processing circuits (41, 43, 45, 50, 70, 80, 90) included in the vehicle behavior prediction device are realized by software. However, it is also possible to prepare the information processing circuit (41, 43, 45, 50, 70, 80, 90) by preparing dedicated hardware for executing the following information processing. Further, the plurality of information processing circuits (41, 43, 45, 50, 70, 80, 90) may be configured by individual hardware. Further, the information processing circuit (41, 43, 45, 50, 70, 80, 90) may also be used as an electronic control unit (ECU) used for other control related to the vehicle.

The processing unit 100 includes a detection integration unit 41, an object tracking unit 43, a road structure identification unit 45, a vehicle behavior prediction unit 50, and a plurality of information processing circuits (41, 43, 45, 50, 70, 80, and 90). The vehicle includes a vehicle route generator 70, a speed profile generator 80, and a vehicle controller 90. Further, the vehicle behavior prediction section 50 includes an intersecting vehicle identification section 51, a preceding vehicle identification section 53, a behavior change detection section 55, a behavior prediction threshold change section 57, and a behavior prediction section 59.

The detection integration unit 41 integrates a plurality of detection results obtained from each of the plurality of object detection sensors included in the object detection unit 21 and outputs one detection result for each object. Specifically, from the behavior of the object obtained from each of the object detection sensors, the most rational behavior of the object with the smallest error is calculated in consideration of the error characteristics of each object detection sensor. Specifically, by using a known sensor fusion technique, detection results obtained by a plurality of types of sensors are comprehensively evaluated to obtain more accurate detection results.

In addition, when the detected object is a vehicle, the detection integration unit 41 may detect the behavior of the vehicle by detecting whether the winker is lit or not.

The object tracking unit 43 tracks the object detected by the detection integration unit 41. Specifically, the object tracking unit 43 verifies (corresponds) the identity of the object between different times from the behavior of the object output at different times, and tracks the object based on the correspondence. I do.

The road structure identification unit 45 determines the type of the road structure on the planned traveling route of the own vehicle from the absolute position of the own vehicle obtained by the own vehicle position estimation unit 23 and the map data obtained by the map information obtaining unit 25. Identify. For example, the road structure specifying unit 45 specifies an intersection, a junction with a merging lane, a T-shaped road, and the like on the scheduled travel route of the vehicle. In addition, the road structure specifying unit 45 may specify the position and the type of the traffic light installed at the intersection, or specify the priority lane and the non-priority lane from the lanes in the road structure. It may be something.

Based on the object information acquired from the object tracking unit 43 and the type of the road structure identified by the road structure identification unit 45, the intersecting vehicle identification unit 51 runs the own vehicle from the object detected by the object detection unit 21. An intersecting vehicle having a scheduled traveling route that intersects the scheduled route is specified. As a premise for specifying an intersecting vehicle in the intersecting vehicle specifying unit 51, it is assumed that the scheduled traveling route of the own vehicle has already been generated. In addition, it is assumed that the planned traveling route of the intersecting vehicle is also provisionally generated based on the object information and the road information acquired from the object tracking unit 43. The planned traveling route of the crossing vehicle is, for example, when an object is detected on the right turn lane of the oncoming lane at the intersection on the planned travel route of the own vehicle, or when an object is detected at a position on the extension of the right turn lane within the intersection. In addition, it is possible for the intersecting vehicle to generate a right-turn route from the right-turn lane in the oncoming lane as the scheduled traveling route.

Based on the object information acquired from the object tracking unit 43 and the type of the road structure obtained by the road structure identification unit 45, the preceding vehicle identification unit 53 determines the scheduled travel route of the vehicle from the object detected by the object detection unit 21. Identify the traveling preceding vehicle. For example, a preceding vehicle running ahead of the own vehicle is specified.

The behavior change detection unit 55 detects a change in the behavior of the preceding vehicle with respect to the preceding vehicle identified by the preceding vehicle identification unit 53 based on the time change of the object information acquired from the object tracking unit 43.

The above-described method for specifying an intersecting vehicle, the method for specifying a preceding vehicle, and the method for detecting a change in behavior of the preceding vehicle are variously changed based on the type of road structure.

The behavior prediction threshold changing unit 57 determines whether or not there is a preceding vehicle, the positional relationship between the own vehicle and another vehicle (including the preceding vehicle and the crossing vehicle), road information, the behavior change of the preceding vehicle detected by the behavior change detection unit 55, and the like. , A behavior prediction threshold T (first threshold) is set. The details of the setting of the behavior prediction threshold T in the behavior prediction threshold changing unit 57 will be described later.

The behavior prediction unit 59 calculates an index value for predicting the entry of an intersecting vehicle into the planned traveling route of the own vehicle based on the object information acquired from the object tracking unit 43. For example, when the preceding vehicle does not exist, the time until the own vehicle reaches the intersection of the planned travel route of the own vehicle and the planned travel route of the crossing vehicle is calculated as the index value. If there is a preceding vehicle, it is a section on the traveling route of the own vehicle, such as a headway time (THW: Time @ Headway) and a time to collision (TTC: Time @ to \ Collision) of the own vehicle with respect to the preceding vehicle. An index value indicating a distance between the vehicle and the own vehicle is calculated.

Then, the behavior prediction unit 59 determines whether or not the intersecting vehicle enters the scheduled travel route of the own vehicle based on the behavior prediction threshold T set in the behavior prediction threshold changing unit 57 and the calculated index value. Predict. The details of the approach prediction of the crossing vehicle in the behavior prediction unit 59 will be described later.

The own vehicle route generating unit 70 generates a scheduled travel route of the own vehicle based on the object information acquired from the object tracking unit 43, the map information acquired by the map information acquiring unit 25, and the position of the own vehicle.

Here, when the vehicle behavior prediction unit 50 predicts whether or not an intersecting vehicle will enter the scheduled travel route of the own vehicle, the own vehicle route generation unit 70 performs the object information, the map information, Based on the prediction result by the vehicle behavior prediction unit 50 in addition to the position, the travel schedule of the own vehicle is generated.

Based on the object information acquired from the object tracking unit 43, the map information acquired by the map information acquisition unit 25, and the position of the own vehicle, the speed profile generation unit 80 generates a speed profile when the own vehicle travels on the planned traveling route. Generate. Here, the speed profile is data indicating how the speed of the host vehicle changes when the host vehicle moves along the planned traveling route.

Here, when the vehicle behavior prediction unit 50 predicts whether or not an intersecting vehicle will enter the scheduled travel route of the own vehicle, the own vehicle route generation unit 70 performs the object information, the map information, Based on the prediction result by the vehicle behavior prediction unit 50 in addition to the position, a speed profile when the own vehicle travels on the planned traveling route is generated.

The vehicle control unit 90 performs vehicle control on the own vehicle based on the scheduled traveling route generated by the own vehicle route generation unit 70 and the speed profile generated by the speed profile generation unit 80.

[Processing procedure of vehicle behavior prediction]
Next, the processing procedure of the vehicle behavior prediction according to the present embodiment will be described using the flowchart of FIG. The vehicle behavior prediction process shown in FIG. 2 is started when the ignition of the host vehicle is turned on, and is repeatedly executed while the ignition is on.

First, in step S101, the crossing vehicle specifying unit 51 specifies a crossing vehicle. In addition, when the scheduled travel route of the own vehicle is not generated, for example, immediately after the ignition of the own vehicle is turned on, the crossing vehicle specifying unit 51 does not specify the crossing vehicle.

Next, in step S103, the vehicle behavior prediction unit 50 determines whether or not the specified intersecting vehicle exists. If the specified crossing vehicle exists (YES in step S103), the processing in FIG. 2 proceeds to step S105. On the other hand, when there is no specified intersecting vehicle (NO in step S103), the process of predicting the vehicle behavior of the intersecting vehicle ends.

In step S105, the preceding vehicle specifying unit 53 specifies the preceding vehicle.

In step S107, the vehicle behavior prediction unit 50 determines whether the specified preceding vehicle exists. If the specified preceding vehicle exists (YES in step S107), the processing in FIG. 2 proceeds to step S109. On the other hand, if the specified preceding vehicle does not exist (NO in step S107), the process proceeds to step S115.

In step S109, the behavior change detection unit 55 detects a behavior change of the preceding vehicle.

In step S111, the vehicle behavior prediction unit 50 determines whether or not the behavior of the preceding vehicle has changed. If there is a change in the behavior of the preceding vehicle (YES in step S111), the process in FIG. 2 proceeds to step S113. On the other hand, if there is no change in the behavior of the preceding vehicle (NO in step S111), the process proceeds to step S115.

In step S113, the behavior prediction threshold changing unit 57 changes the behavior prediction threshold T based on the detected behavior change of the preceding vehicle.

In step S115, the behavior prediction unit 59 predicts the behavior of the crossing vehicle. As the behavior of the crossing vehicle, for example, it is predicted whether or not the crossing vehicle will enter the planned traveling route of the own vehicle.

Based on the behavior of the intersecting vehicle predicted based on the above-described processing, the own vehicle route generation unit 70 generates a scheduled travel route of the own vehicle, and the speed profile generation unit 80 determines whether the own vehicle travels along the scheduled travel route. Generate a speed profile for Further, the vehicle control unit 90 performs vehicle control on the own vehicle based on the generated planned traveling route and speed profile of the own vehicle.

[Setting of threshold for behavior prediction]
Next, the setting of the behavior prediction threshold T in the behavior prediction threshold changing unit 57 will be specifically described.

The behavior prediction threshold value T (first threshold value) is determined based on the presence / absence of the preceding vehicle, the positional relationship of the own vehicle and other vehicles (including the preceding vehicle and the crossing vehicle), road information, and the preceding vehicle detected by the behavior change detection unit 55. Is set based on a disturbance factor such as a change in the behavior of the vehicle. This is because the probability of the crossing vehicle entering the scheduled traveling route of the own vehicle can be changed by such a disturbance factor.

For example, as shown by a curve F1 in FIG. 3, the approach probability of the crossing vehicle with respect to the planned traveling route of the own vehicle is determined until the vehicle reaches a position where the planned traveling route of the own vehicle and the planned traveling route of the crossing vehicle intersect. , And changes depending on an index value such as THW and TTC of the own vehicle with respect to the preceding vehicle. The larger the index value, the more safely the crossing vehicle can enter the scheduled travel route of the own vehicle, and thus the higher the probability of the crossing vehicle entering.

Therefore, when the preceding vehicle does not exist, the behavior prediction threshold value changing unit 57 determines whether or not the intersection vehicle and the intersection vehicle have a 50% probability of entering the intersection vehicle with respect to the intersection vehicle. The time until the host vehicle reaches the position where the planned traveling route intersects is set as the behavior prediction threshold T.

In addition, when there is no change in the behavior of the preceding vehicle, the behavior prediction threshold changing unit 57 sets the THW of the own vehicle to the preceding vehicle or the THW of the own vehicle to the preceding vehicle when the approach probability of the crossing vehicle with respect to the planned route of the own vehicle becomes 50%. TTC is set as the behavior prediction threshold T.

As shown by the curve F1 in FIG. 3, the approach probability of the crossing vehicle when the index value is equal to or larger than the behavior prediction threshold T is equal to or greater than the entry probability when the index value is equal to the behavior prediction threshold T. Therefore, when the index value is equal to or greater than the behavior prediction threshold T, it can be predicted that the crossing vehicle will enter the scheduled travel route of the host vehicle.

On the other hand, the entry probability of the crossing vehicle when the index value is less than the behavior prediction threshold T is a value less than the entry probability when the index value is equal to the behavior prediction threshold T. Therefore, when the index value is less than the behavior prediction threshold value T, it can be predicted that the crossing vehicle will not enter the scheduled travel route of the own vehicle.

Thus, by comparing the index value and the behavior prediction threshold value T, it is possible to predict whether or not the crossing vehicle will enter the planned traveling route of the own vehicle.

The behavior prediction threshold value T set as described above includes the positional relationship of the own vehicle and another vehicle (including a preceding vehicle and an intersecting vehicle), road information, a behavior change of the preceding vehicle detected by the behavior change detection unit 55, and the like. It is changed by the behavior prediction threshold changing unit 57 based on the disturbance factor.

For example, suppose that the relationship between the index value and the entry probability changes from the curve F1 in FIG. 3 to the curve F2 due to the influence of the disturbance factor. Here, the value of the behavior prediction threshold T determined based on the curve F1 is “Tc”, and the value of the behavior prediction threshold T determined based on the curve F2 is “Tc−Δ”.

When predicting the approach of an intersecting vehicle under the influence of a disturbance factor, the value of the behavior prediction threshold T is set to “Tc” despite the relationship between the index value and the approach probability changing from the curve F1 to the curve F2. ”, The accuracy of the prediction of the approach of the crossing vehicle is lost. Therefore, the behavior prediction threshold changing unit 57 determines the correction amount Δ based on the type and the degree of influence of the disturbance factor, and changes the value of the behavior prediction threshold T from “Tc” to correct “Tc−Δ”. . As is clear from the direction of the sign, as the correction amount Δ increases, the changed behavior prediction threshold T decreases.

As described above, by changing the value of the behavior prediction threshold value T according to the correction amount Δ, it is possible to improve the accuracy of the prediction of the entry of the crossing vehicle when there is an influence of a disturbance factor.

タイミング The timing at which the behavior of the preceding vehicle changes does not always coincide with the reference time for predicting the approach of the crossing vehicle. For example, there is a possibility that a change in the vehicle speed of the preceding vehicle occurs after a change in the behavior of the preceding vehicle occurs, and the positional relationship between the host vehicle and the other vehicle changes. In order to improve the accuracy of the prediction of the entry of the crossing vehicle, it is preferable to consider the positional relationship of the own vehicle and other vehicles, the road information, and the like at the time of the reference of the prediction of the entry of the crossing vehicle in determining the correction amount Δ.

[Estimation of approach of crossing vehicles]
Next, the approach prediction of the crossing vehicle by the behavior prediction unit 59 will be specifically described.

The behavior predicting unit 59 calculates an index value such as a time required for the vehicle to reach a position where the planned traveling route of the own vehicle and a planned traveling route of the crossing vehicle intersect, and the THW and TTC of the own vehicle with respect to the preceding vehicle.

Note that, in order to improve the accuracy of the prediction of the approach of the crossing vehicle, it is preferable that the reference time of the calculation of the index value and the reference time of the prediction of the approach of the crossing vehicle match and approach as much as possible. This is because if a change in the vehicle speed of the preceding vehicle occurs between the reference time for calculating the index value and the reference time for predicting the approach of the crossing vehicle, it may affect the accuracy of the prediction of the approach of the crossing vehicle. .

When the calculated index value is equal to or greater than the behavior prediction threshold T, the behavior prediction unit 59 predicts that an intersecting vehicle will enter the planned traveling route of the own vehicle. On the other hand, when the calculated index value is less than the threshold value T for behavior prediction, the behavior prediction unit 59 predicts that the crossing vehicle will not enter the scheduled travel route of the own vehicle.

In addition, the behavior prediction unit 59 may predict the time at which the crossing vehicle starts to enter the scheduled travel route of the own vehicle based on the calculated index value and the behavior prediction threshold T.

For example, if the calculated index value is equal to or greater than the behavior prediction threshold value T, the vehicle crosses the position before the vehicle passes through the intersection of the planned travel route of the own vehicle and the planned travel route of the intersecting vehicle. Is thought to pass. Therefore, the behavior prediction unit 59 may predict a time that is a predetermined time before the scheduled time at which the own vehicle passes the position as a time at which the crossing vehicle starts to enter.

If the calculated index value is smaller than the behavior prediction threshold T, the vehicle crosses the intersection of the planned traveling route of the own vehicle and the planned traveling route of the intersecting vehicle, and then the crossing vehicle passes the position. It is thought to pass. Therefore, the behavior prediction unit 59 may predict a time that is a predetermined time later than the scheduled time at which the own vehicle will pass through the position as a time at which the crossing vehicle starts to enter.

[Control based on predicted results of approaching crossing vehicles]
When the vehicle behavior prediction unit 50 predicts whether or not an intersecting vehicle will enter the planned traveling route of the own vehicle, the own vehicle route generation unit 70 adds the object information, the map information, and the own position. Then, based on the prediction result by the vehicle behavior prediction unit 50, the scheduled travel route of the own vehicle is generated. For example, when the probability of the crossing vehicle entering the scheduled travel route of the own vehicle is equal to or higher than the danger level value, the vehicle may travel before the intersection of the scheduled travel route of the own vehicle and the scheduled travel route of the crossed vehicle. The vehicle control unit 90 may control the own vehicle such that the vehicle is decelerated.

Further, when it is predicted that the intersecting vehicle does not enter the planned traveling route of the own vehicle, the vehicle control unit 90 controls the own vehicle so as to avoid a situation where the intersecting vehicle enters the planned traveling route of the own vehicle contrary to the prediction result. May be controlled. Specifically, when the calculated index value is less than the behavior prediction threshold T and the absolute value of the difference between the index value and the behavior prediction threshold T is equal to or smaller than a predetermined value, the vehicle control unit 90 Control for reducing the inter-vehicle distance between the own vehicles may be performed. As the inter-vehicle distance between the preceding vehicle and the own vehicle decreases, the approach probability of the intersecting vehicle decreases, so that it is possible to suppress the possibility that a situation contrary to the prediction result will occur.

Further, when it is predicted that the crossing vehicle will enter the planned traveling route of the own vehicle, the vehicle control unit 90 controls the own vehicle so as to avoid a situation in which the crossing vehicle does not enter the planned traveling route of the own vehicle contrary to the prediction result. It may be controlled. Specifically, when the calculated index value is equal to or larger than the behavior prediction threshold T and the absolute value of the difference between the index value and the behavior prediction threshold T is equal to or smaller than a predetermined value, the vehicle control unit 90 Control for increasing the inter-vehicle distance between the own vehicles may be performed. As the inter-vehicle distance between the preceding vehicle and the host vehicle increases, the approach probability of the intersecting vehicle increases, so that it is possible to suppress the possibility that a situation contrary to the prediction result will occur.

[Example of vehicle behavior prediction for each driving scene]
Next, an example of vehicle behavior prediction for each traveling scene will be described with reference to FIGS.

(First driving scene)
First, the vehicle behavior prediction will be described based on the “first driving scene” in FIG. In FIG. 4, before the intersection, the own vehicle VS and the vehicle VB are traveling in the lane TL1, and the vehicle VC is entering the intersection and traveling from the lane TL3 to the lane TL5 or the lane TL6. It is shown.

において In FIG. 4, lanes TL1 and TL3 are lanes that can be turned left or straight, and lanes TL2 and TL4 are lanes dedicated to right turns.

(4) The road structure specifying unit 45 specifies an intersection existing on the planned traveling route of the host vehicle VS based on the road information. In FIG. 4, lanes TL1 to TL4 intersect with lanes TL5 and TL6 at the intersection. Further, it indicates whether or not the vehicle can turn in one direction, which is a direction from the oncoming road toward the own vehicle road, on opposite roads (lane TL3, lane TL4) facing the own vehicle road (lane TL1, TL2) on which the own vehicle VS runs. Specify that there is no left / right turn signal. Here, “one direction” is a left turn direction for the own vehicle VS and the vehicle VB, and is a right turn direction for the vehicle VC.

When there is no right / left turn signal indicating whether or not turning in one direction is possible on the opposite road, the behavior of the vehicle VC traveling on the opposite road and turning in one direction within the intersection is determined by running on the own road and entering the intersection. Is considered to be affected by the behavior of the vehicle VB.

Based on the behavior of the vehicle VC traveling on the opposite road acquired from the object tracking unit 43, the intersection vehicle identification unit 51 determines whether the vehicle VC is scheduled to turn at the intersection. Then, when the vehicle VC is scheduled to turn in one direction (scheduled to turn right), the intersecting vehicle specifying unit 51 specifies the vehicle VC as an intersecting vehicle to be subjected to vehicle behavior prediction.

Note that the vehicle VC may be specified as the target intersecting vehicle based on the fact that the vehicle VC is traveling in the lane TL4, which is a lane dedicated to right turns. The absolute value of the difference between the arrival time of the vehicle VC at a position where the planned traveling route of the vehicle VC and the planned traveling route of the own vehicle VS intersect and the arrival time of the own vehicle VS at the position is a predetermined value (for example, 1 second). ) Based on the following, the vehicle VC may be specified as an intersecting vehicle.

Further, when the vehicle VC performs an operation of moving in one direction from the lane center of the lane TL4 (moving operation), when the vehicle VC performs a deceleration operation, or when the vehicle VC turns in one direction. The vehicle VC may be specified as an intersecting vehicle, for example, when the indicated blinker display operation is performed. Further, the vehicle VC may be specified as an intersecting vehicle based on the arrival time at the intersection of the vehicle VC.

The preceding vehicle specifying unit 53 calculates the THW of the own vehicle VS with respect to the vehicle VB and the arrival time to the intersection of the vehicle VB based on the behavior of the vehicle VB traveling on the own vehicle road acquired from the object tracking unit 43. . Then, the preceding vehicle specifying unit 53 determines that the THW of the host vehicle VS with respect to the vehicle VB is equal to or smaller than the filtering threshold A1 (second threshold), and the arrival time at the intersection of the vehicle VB is the filtering threshold A2 (third threshold). ) In the following cases, the vehicle VB is specified as a preceding vehicle to be subjected to vehicle behavior prediction. Further, the preceding vehicle specifying unit 53 determines that the vehicle VB is ahead of the host vehicle VS.

Here, the reason for making the determination using the filtering threshold A1 is to perform the vehicle behavior prediction processing only for the preceding vehicle that may affect the behavior of the own vehicle. The threshold value A1 for filtering is preferably about 7 to 8 seconds from the statistical result.

The reason for making the determination using the filtering threshold value A2 is to perform the vehicle behavior prediction processing only on the preceding vehicle that may affect the behavior of the crossing vehicle. The threshold value A2 for filtering is determined based on the running scene, and it is typically desirable to set the threshold value to about 10 seconds.

The behavior change detection unit 55 detects a change in the behavior of the vehicle VB specified as the preceding vehicle based on the time change of the object information acquired from the object tracking unit 43. Specifically, behavior change detecting section 55 detects a turning preliminary operation of vehicle VB.

For example, an operation (moving operation) in which the vehicle VB moves in one direction from the center of the lane TL1 (moving operation) may be detected as a turning preliminary operation of the vehicle VB. Here, the operation of moving in one direction is determined by dividing a distance from the lane center of the lane TL1 measured in the lane width direction to the vehicle center of the vehicle VB by the lane width to a predetermined threshold (for example, 0.3). The determination may be based on whether the above is true.

Further, the vehicle VB may detect a deceleration operation (for example, a deceleration operation in which the acceleration of the vehicle VB is equal to or less than the threshold value “−20 km / h ＾ 2”) as the turning preparatory operation of the vehicle VB.

The operation of the blinker display indicating that the vehicle VB turns in one direction may be detected as a preparatory turn operation of the vehicle VB.

The behavior prediction threshold changing unit 57 determines whether there is a preceding vehicle, the positional relationship between the own vehicle and another vehicle (including the preceding vehicle and the crossing vehicle), road information, and the behavior change of the preceding vehicle detected by the behavior change detection unit 55. The correction amount Δ is determined based on the disturbance factor, and the value of the behavior prediction threshold T is increased or decreased.

In the “first driving scene” of FIG. 4, since the vehicle VB specified as the preceding vehicle exists, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, the correction amount Δ is set to one second). increase).

車 The lanes that the vehicles VB and VC can enter after passing through the intersection are the lanes TL5 and TL6. Therefore, it can be determined that the number of lanes that the vehicle VB and the vehicle VC can enter after passing through the intersection is two or more, and that there is sufficient space at the destination of the vehicle VC. Therefore, it is considered that the entry probability of the vehicle VC increases. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 second).

Further, if there are two or more lanes on the own vehicle road except the lane TL2, which is the lane on which the vehicle to be turned in the opposite direction runs, the vehicle VC intersects at the intersection. Since the number of lanes to be increased increases, the time for the vehicle VC to pass through the intersection becomes longer. In this case, since the approach probability of the vehicle VC is considered to be small, the behavior prediction threshold changing unit 57 increases the behavior prediction threshold T (for example, decreases the correction amount Δ by 0.5 second).

Also, if two or more vehicles scheduled to enter the intersection behind the vehicle VC are waiting, the entry probability of the vehicle VC becomes large in order to eliminate the waiting state of the vehicle behind the vehicle VC. Conceivable. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 seconds).

Further, if the oncoming road is a one-lane road on one side and a vehicle that is scheduled to enter the intersection behind the vehicle VC is on standby, the standby state of the vehicle behind the vehicle VC is changed. It is considered that the approach probability of the vehicle VC increases to solve the problem. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 seconds).

Also, if five or more vehicles that are scheduled to enter the intersection behind the vehicle VB are waiting, the vehicle VC is set in order to avoid waiting of the vehicle VC due to the vehicle entering the intersection behind the vehicle VB. It is considered that the probability of entry will increase. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 seconds).

The behavior prediction threshold changing unit 57 confirms that the value of the behavior prediction threshold T after the increase / decrease change as described above falls within a range suitable for use in predicting the approach of an intersecting vehicle ( For example, it is confirmed that the behavior prediction threshold T is equal to or less than the upper limit value of 8 seconds and equal to or more than the lower limit value of 4 seconds. If it is within the appropriate range, the process of changing the behavior prediction threshold T ends.

Note that the behavior prediction threshold T may be dynamically determined by calculation using the position, attitude, speed, acceleration, and road structure of the own vehicle and the other vehicles.

In the “first driving scene”, the shape of the road is described as two lanes on one side. However, the present invention is not limited to this, and an intersection without one lane or one lane or three lanes on one side may be used. Although the description has been made on the assumption that the vehicle is driven on the left side, the invention is not limited to this. In a country where right-hand traffic is legally maintained, a preceding vehicle may be a right-turning vehicle and an intersecting vehicle may be a left-turning vehicle. Furthermore, although the description has been given on the assumption that the object is an automobile, the object may be a motorcycle or a light vehicle. Further, it may be an intersection without a traffic light or an intersection with a traffic signal.

(Second running scene)
Next, vehicle behavior prediction will be described based on the “second driving scene” in FIG. FIG. 5 shows a situation where the lane TL7 in which the host vehicle VS and the vehicle VB travel and the lane TL8 in which the vehicle VC travels merge.

The road structure specifying unit 45 specifies a lane TL8 that merges with the lane TL7 where the host vehicle VS travels at the junction based on the road information as a merging lane. Then, the intersecting vehicle specifying unit 51 specifies the vehicle VC running on the lane TL8 specified as the merging lane as the intersecting vehicle to be subjected to the vehicle behavior prediction.

It should be noted that the absolute value of the difference between the arrival time of the vehicle VC at a position where the planned traveling route of the vehicle VC and the planned traveling route of the own vehicle VS intersect and the arrival time of the own vehicle VS at the position is a predetermined value (for example, (1 second) or less, the vehicle VC may be specified as an intersecting vehicle.

Based on the behavior of the vehicle VB in front of the host vehicle VS acquired from the object tracking unit 43, the preceding vehicle specifying unit 53 calculates the THW of the host vehicle VS with respect to the vehicle VB and the arrival time to the junction of the vehicle VB. Is calculated. Then, the preceding vehicle specifying unit 53 determines that the THW of the host vehicle VS with respect to the vehicle VB is equal to or smaller than the filtering threshold A1 (second threshold), and the arrival time at the intersection of the vehicle VB is the filtering threshold A2 (third threshold). ) In the following cases, the vehicle VB is specified as a preceding vehicle to be subjected to vehicle behavior prediction. The reason for making the determination using the filtering threshold A1 and the filtering threshold A2 is the same as in the case of the “first driving scene”.

Instead of making the determination using the filtering threshold A1 and the filtering threshold A2, the preceding vehicle specifying unit 53 determines the headway time or the headway time of the vehicle VB before passing the junction and passing the junction. The vehicle VB whose collision margin time is equal to or smaller than the filtering threshold B1 (fourth threshold) may be specified as a preceding vehicle to be subjected to vehicle behavior prediction.

The behavior change detection unit 55 detects a change in the behavior of the vehicle VB specified as the preceding vehicle based on the time change of the object information acquired from the object tracking unit 43.

For example, the vehicle VB may detect an acceleration operation (for example, an operation in which the acceleration of the vehicle VB is equal to or more than a threshold “10 km / h ＾ 2”) as a change in the behavior of the vehicle VB.

The behavior prediction threshold changing unit 57 determines whether there is a preceding vehicle, the positional relationship between the own vehicle and another vehicle (including a preceding vehicle and an intersecting vehicle), road information, the behavior change of the preceding vehicle detected by the behavior change detection unit 55, and the like. The correction amount Δ is determined based on the disturbance factor, and the value of the behavior prediction threshold T is increased or decreased.

In the “second running scene” in FIG. 5, since the vehicle VB specified as the preceding vehicle exists, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, the correction amount Δ is reduced by one second). increase).

(4) The behavior prediction threshold changing unit 57 detects a pre-merging operation of the vehicle VC.

For example, an operation (moving operation) in which the vehicle VC moves toward the lane TL7, which is the lane to be merged, from the center of the lane TL8 may be detected as a preliminary operation for merging the vehicle VC. Here, the operation of moving toward the lane to be merged is determined by dividing a distance from the lane center of the lane TL8 measured in the lane width direction to the vehicle center of the vehicle VC by the lane width to a predetermined threshold (for example, 0. 3) The determination may be based on whether the above is the case.

Further, the vehicle VC may detect an acceleration operation (for example, an operation in which the acceleration of the vehicle VC is equal to or greater than the threshold value “10 km / h ＾ 2”) as a consolidation preliminary operation of the vehicle VC.

The operation of the blinker display indicating that the vehicle VC turns toward the merging target lane may be detected as the merging preliminary operation of the vehicle VC.

場合 When the vehicle VC indicates the above-described joint preparatory operation, the entry probability of the vehicle VC is considered to increase. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 second).

Even if the vehicle VC does not indicate the above-described merging preparatory operation, as a result of the vehicle VC approaching the end point of the merging lane, the time until the vehicle VC reaches the merging point is equal to the filtering threshold B2. When it becomes equal to or less than the (fifth threshold), it is considered that the approach probability of the vehicle VC increases. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 second).

Further, when the speed of the vehicle VC is higher than the speed of the host vehicle VS by a predetermined ratio or more (for example, 20% or more), it is considered that the entry probability of the vehicle VC increases. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 second).

As described above, in the “second driving scene”, the case where the lanes merge is described. However, the present invention is not limited to this. For example, the road width decreases due to the presence of a construction vehicle or a parked vehicle on the road. It may be the case.

(Third driving scene)
Next, the "third running scene" will be described as an example. In FIG. 6, just before the T-shaped road, the own vehicle VS and the vehicle VB are traveling on the lane TL9, and the vehicle VC enters the intersection of the T-shaped road and moves from the lane TL12 to the lane TL13 or the lane TL14. Is running.

In FIG. 6, the lane TL9 is a lane that allows both left turning and straight ahead, and the lane TL10 is a lane dedicated to straight ahead.

(4) The road structure specifying unit 45 specifies a T-shaped road existing on the scheduled traveling route of the host vehicle VS based on the road information. In FIG. 6, at the intersection of the T-shaped road, the lanes TL9, TL10, TL13, and TL14 are the priority lanes, while the lanes TL11 and TL12 have the lower priority than the priority lanes. It is a priority lane.

Based on the behavior of the vehicle VC traveling on the lane TL12, which is the non-priority lane, acquired from the object tracking unit 43, the intersecting vehicle identification unit 51 determines whether the vehicle VC is scheduled to enter the intersection of the T-shaped road. When it is determined that the vehicle VC is scheduled to enter the intersection of the T-junction,
The intersecting vehicle specifying unit 51 specifies the vehicle VC as an intersecting vehicle to be subjected to vehicle behavior prediction.

Note that the vehicle VC may be specified as the target intersecting vehicle based on the fact that the vehicle VC is traveling in the lane TL12 which is a non-priority lane. The absolute value of the difference between the arrival time of the vehicle VC at a position where the planned traveling route of the vehicle VC and the planned traveling route of the own vehicle VS intersect and the arrival time of the own vehicle VS at the position is a predetermined value (for example, 1 second). ) Based on the following, the vehicle VC may be specified as an intersecting vehicle.

In addition, when the vehicle VC moves out of the lane center of the lane TL12 and moves to the end of the lane TL12 (moving operation), when the vehicle VC performs a deceleration operation, or in a blinker display indicating that the vehicle VC is turning, The vehicle VC may be specified as an intersecting vehicle when an operation is performed. Further, the vehicle VC may be specified as an intersecting vehicle based on the arrival time at the intersection of the vehicle VC.

The preceding vehicle specifying unit 53 calculates the THW of the own vehicle VS with respect to the vehicle VB and the arrival time to the intersection of the vehicle VB based on the behavior of the vehicle VB traveling on the own vehicle road acquired from the object tracking unit 43. . Then, the preceding vehicle specifying unit 53 determines that the THW of the host vehicle VS with respect to the vehicle VB is equal to or less than the filtering threshold A1 (second threshold), and that the arrival time of the vehicle VB at the intersection of the T-shaped road is the filtering threshold A2. If it is equal to or less than the (third threshold), the vehicle VB is specified as the preceding vehicle to be subjected to the vehicle behavior prediction. Further, the preceding vehicle specifying unit 53 determines that the vehicle VB is ahead of the host vehicle VS. The reason for making the determination using the filtering threshold A1 and the filtering threshold A2 is the same as in the case of the “first driving scene”.

The behavior change detection unit 55 detects a change in the behavior of the vehicle VB specified as the preceding vehicle based on the time change of the object information acquired from the object tracking unit 43, as in the case of the “first running scene”.

In the “third running scene” in FIG. 6, since the vehicle VB specified as the preceding vehicle exists, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, the correction amount Δ is reduced by one second). increase).

The lanes to which the vehicle VC can enter after passing through the intersection of the T-shaped road are the lanes TL9, TL10, TL13, and TL14. Therefore, it can be determined that the number of roads that the vehicle VC can enter after passing through the intersection of the T-junction is two or more lanes, and that there is sufficient space at the destination of the vehicle VC. Therefore, it is considered that the entry probability of the vehicle VC increases. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 second).

Furthermore, if two or more vehicles scheduled to enter the intersection of the T-junction are behind the vehicle VC, the approach of the vehicle VC is canceled in order to cancel the waiting state of the vehicle behind the vehicle VC. The probability is expected to be large. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 seconds).

If the non-priority lane is a road with one lane on each side and a vehicle scheduled to enter an intersection of a T-shaped road behind the vehicle VC is waiting, the vehicle behind the vehicle VC It is considered that the approach probability of the vehicle VC increases in order to eliminate the waiting state of the vehicle VC. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 seconds).

Further, if five or more vehicles scheduled to enter the intersection of the T-shaped road behind the vehicle VB are waiting, the vehicle VC behind the vehicle VB is prevented from entering the intersection to avoid waiting. It is considered that the entry probability of the vehicle VC increases. Therefore, the behavior prediction threshold changing unit 57 decreases the behavior prediction threshold T (for example, increases the correction amount Δ by 0.5 seconds).

In the “third running scene”, the shape of the road is described as two lanes on one side. However, the present invention is not limited to this, and a T-shaped road having one lane or three lanes or more on one side and no lane may be used. In addition, although the description has been made on the assumption that the vehicle is traveling on the left side, the invention is not limited to this. Furthermore, although the description has been given on the assumption that the object is an automobile, the object may be a motorcycle or a light vehicle. Further, it may be an intersection without a traffic light or an intersection with a traffic signal.

[Effects of Embodiment]
As described in detail above, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment detect an object outside the host vehicle, and, based on the detected object, the travel schedule that intersects the travel route of the host vehicle. Identify an intersecting vehicle having a route and a preceding vehicle traveling on the scheduled route of the own vehicle, detect a change in the behavior of the preceding vehicle, set a first threshold based on the change in the behavior, and set Based on the index value indicating the distance between the preceding vehicle and the own vehicle in the planned route and the first threshold value, the approaching of the crossing vehicle to the planned running route of the own vehicle is predicted.

Thereby, since the prediction is performed in consideration of the influence of the change in the behavior of the preceding vehicle ahead in the traveling direction, the accuracy of the prediction of the approach of the crossing vehicle is improved. Further, by improving the accuracy of the approach prediction, the possibility of sudden deceleration of the own vehicle occurring in control of the own vehicle based on the approach prediction of the crossing vehicle can be reduced.

In addition, the vehicle behavior prediction method and the vehicle behavior prediction apparatus according to the present embodiment may predict that an intersecting vehicle will enter the scheduled travel route of the host vehicle when the index value is equal to or greater than the first threshold. . Therefore, the approach prediction of the crossing vehicle can be realized by a method with a low calculation cost of comparing the index value with the first threshold value.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment predict a time at which an intersecting vehicle starts to enter the planned traveling route of the own vehicle based on the index value and the first threshold value. Is also good. For this reason, information on the entry start time can be obtained together with the entry prediction result, and it is possible to perform more accurate control of the own vehicle when controlling the own vehicle based on the entry prediction of the crossing vehicle.

In addition, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment are based on the map information, and are the intersections on the scheduled travel route of the own vehicle, and the opposite road facing the own vehicle road on which the own vehicle runs. Alternatively, an intersection that does not have a right / left turn signal indicating whether or not it is possible to turn in one direction from the oncoming road to the own vehicle road may be specified. Thereby, the approach prediction of the crossing vehicle can be performed in a traveling scene in which sudden deceleration of the own vehicle easily occurs. As a result, the possibility of sudden deceleration of the host vehicle can be reduced.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may identify a vehicle traveling on an oncoming road and turning in one direction at an intersection as an intersection vehicle. For this reason, it is possible to make an entry prediction for an intersecting vehicle that may cause rapid deceleration of the own vehicle. Further, it is possible to reduce the possibility of sudden deceleration of the vehicle.

The vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may detect a change in behavior of a preceding vehicle based on a preparatory turning operation of the preceding vehicle before entering the intersection. For example, the turning preliminary operation includes a decelerating operation of the preceding vehicle, an operation of moving the preceding vehicle in one direction in the lane in which the preceding vehicle travels, an operation of displaying a right / left turn signal of the preceding vehicle, and the like.

Such a preparatory turning operation of the preceding vehicle can occur at a timing earlier than a change in the behavior of the preceding vehicle actually occurs, and it is necessary to detect a change in the behavior of the preceding vehicle based on the preparatory turning operation of the preceding vehicle. Thus, the approach prediction of the crossing vehicle can be performed at an earlier timing.

In addition, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment, the time until the preceding vehicle starts entering the intersection is less than or equal to the second threshold value, and the collision margin time of the own vehicle with respect to the preceding vehicle The preceding vehicle that is equal to or less than the third threshold may be specified. This makes it possible to exclude a preceding vehicle that is apparently not affecting the own vehicle from being used for the approach prediction. As a result, it is possible to reduce the calculation cost when predicting the approach of the crossing vehicle.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment are configured to perform the first threshold value when the road that the preceding vehicle and the intersecting vehicle enter after passing through the intersection is a road having two or more lanes on one side. May be reduced. If the destination of the crossing vehicle and the preceding vehicle is a road that has two or more lanes on one side, it can be assumed that there is sufficient space at the destination of the crossing vehicle, and it is expected that the probability of entry of the crossing vehicle will increase. Is done. Such a relationship between the road structure and the probability of entry of the intersecting vehicle can be used for the prediction of the entry of the intersecting vehicle, so that the accuracy of the entry prediction can be improved.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment, when two or more vehicles scheduled to enter the intersection are waiting behind the traveling direction of the intersection vehicle before entering the intersection, , The first threshold value may be reduced. In such a case, it is considered that the approaching probability of the crossing vehicle increases in order to eliminate the waiting state of the vehicle behind the crossing vehicle. Since the relationship between the waiting state of the vehicle and the approach probability of the intersecting vehicle can be used for the approach prediction of the intersecting vehicle, the accuracy of the approach prediction can be improved.

Furthermore, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment are configured such that a predetermined number or more vehicles that are scheduled to enter the intersection are waiting behind the traveling direction of the preceding vehicle before entering the intersection. Alternatively, the first threshold value may be reduced. In such a case, the approaching probability of the crossing vehicle is considered to be large in order to avoid the waiting of the crossing vehicle due to the vehicle behind the preceding vehicle entering the intersection. Since the relationship between the waiting state of the vehicle and the approach probability of the intersecting vehicle can be used for the approach prediction of the intersecting vehicle, the accuracy of the approach prediction can be improved.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment are arranged such that a vehicle scheduled to enter the intersection is waiting behind the traveling direction of the intersection vehicle before entering the intersection, and the oncoming road is In the case of one lane on each side, the first threshold value may be reduced. In such a case, it is considered that the approaching probability of the crossing vehicle increases in order to eliminate the waiting state of the vehicle behind the crossing vehicle. Since the relationship between the road structure and the waiting state of the vehicle and the approach probability of the intersecting vehicle can be used for the approach prediction of the intersecting vehicle, the accuracy of the approach prediction can be improved.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment are arranged such that the road on which the preceding vehicle and the own vehicle travel is two lanes on each side except for the lane on which the vehicle scheduled to turn in a direction opposite to one direction travels. When the vehicle is composed of the above lanes, the first threshold may be increased. In this case, the number of lanes where the intersecting vehicles intersect within the intersection increases, so that the time for the vehicle VC to pass through the intersection increases. In this case, it is considered that the approach probability of the vehicle VC decreases. Such a relationship between the road structure and the approach probability of the intersecting vehicle can be used for the approach prediction of the intersecting vehicle, so that the accuracy of the approach prediction can be improved.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may specify a merging lane that merges with a lane in which the preceding vehicle and the own vehicle travel at a merging point based on the map information. . Thereby, the approach prediction of the crossing vehicle can be performed in a traveling scene in which sudden deceleration of the own vehicle easily occurs. As a result, the possibility of sudden deceleration of the host vehicle can be reduced.

Further, the vehicle behavior prediction method and the vehicle behavior prediction apparatus according to the present embodiment may detect a change in behavior of the preceding vehicle based on the acceleration operation of the preceding vehicle before passing through the junction. By detecting a change in the behavior of the preceding vehicle based on the acceleration operation of the preceding vehicle, it is possible to predict the entry of the crossing vehicle at an earlier timing.

In addition, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment are a preceding vehicle before passing the junction, and the headway time of the own vehicle when passing the junction is equal to or less than the fourth threshold. Such a preceding vehicle may be specified. This makes it possible to exclude a preceding vehicle that is apparently not affecting the own vehicle from being used for the approach prediction. As a result, it is possible to reduce the calculation cost when predicting the approach of the crossing vehicle.

Furthermore, the vehicle behavior prediction method and the vehicle behavior prediction apparatus according to the present embodiment are configured to use the preceding vehicle before passing the junction, and the time to allow collision with the own vehicle when passing the junction when the collision margin time is equal to or less than the fourth threshold. A certain preceding vehicle may be specified. This makes it possible to exclude a preceding vehicle that is apparently not affecting the own vehicle from being used for the approach prediction. In particular, since the preceding vehicle is specified by using the time to collision instead of the headway time, the preceding vehicle that clearly does not affect the own vehicle based on the speed change of the preceding vehicle is used for the approach prediction. Can be excluded from use. As a result, it is possible to reduce the calculation cost when predicting the approach of the crossing vehicle.

In addition, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may specify a vehicle traveling on a merging lane before passing a merging point as an intersecting vehicle. For this reason, it is possible to make an entry prediction for an intersecting vehicle that may cause rapid deceleration of the own vehicle. Further, it is possible to reduce the possibility of sudden deceleration of the vehicle.

Furthermore, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may set the first threshold when the crossing vehicle whose time to reach the junction is equal to or less than the fifth threshold does not indicate the consolidation preliminary operation. It may be a reduction. When the intersecting vehicle approaches the end point of the merging lane, it is considered that the approaching probability of the intersecting vehicle increases even when the intersecting vehicle does not show the merging preparatory operation. Such a relationship between the road structure and the approach probability of the intersecting vehicle can be used for the approach prediction of the intersecting vehicle, so that the accuracy of the approach prediction can be improved.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may decrease the first threshold value when the speed of the crossing vehicle is higher than the speed of the own vehicle by a predetermined ratio or more. . In this case, it is considered that the approach probability of the crossing vehicle increases. Such a property that the speed relationship between the own vehicle and the intersecting vehicle gives to the approaching probability of the intersecting vehicle can be used for the approach prediction of the intersecting vehicle, so that the accuracy of the approach prediction can be improved.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may specify a T-junction on the planned traveling route of the own vehicle based on the map information. Thereby, the approach prediction of the crossing vehicle can be performed in a traveling scene in which sudden deceleration of the own vehicle easily occurs. As a result, the possibility of sudden deceleration of the host vehicle can be reduced.

In addition, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment perform the T-shaped operation by traveling in a non-priority lane having a lower priority than the lane in which the vehicle travels among a plurality of roads merging at the T-shaped road. Vehicles scheduled to enter the road may be specified as crossing vehicles. For this reason, it is possible to make an entry prediction for an intersecting vehicle that may cause rapid deceleration of the own vehicle. Further, it is possible to reduce the possibility of sudden deceleration of the vehicle.

Further, the vehicle behavior prediction method and the vehicle behavior prediction device according to the present embodiment may detect a behavior change of a preceding vehicle based on a preparatory turning operation of the preceding vehicle before entering a T-shaped intersection. . For example, the turning preliminary operation includes a decelerating operation of the preceding vehicle, an operation of moving the preceding vehicle in one direction in the lane in which the preceding vehicle travels, an operation of displaying a right / left turn signal of the preceding vehicle, and the like.

In addition, the vehicle behavior prediction method and the vehicle behavior prediction apparatus according to the present embodiment may be configured such that the time until the preceding vehicle starts entering the T-shaped intersection is equal to or less than the second threshold value, and the vehicle has a collision margin with the preceding vehicle. The preceding vehicle whose time is equal to or less than the third threshold may be specified. This makes it possible to exclude a preceding vehicle that is apparently not affecting the own vehicle from being used for the approach prediction. As a result, it is possible to reduce the calculation cost when predicting the approach of the crossing vehicle.

Furthermore, in the vehicle control method using the vehicle behavior prediction method according to the present embodiment and the vehicle control device using the vehicle behavior prediction device, the probability of entry of the crossing vehicle into the scheduled travel route of the own vehicle is equal to or higher than the danger level value. In this case, the vehicle may be decelerated before traveling at a position where the planned traveling route of the own vehicle and the planned traveling route of the crossing vehicle intersect. This makes it possible to decelerate the own vehicle in advance before the crossing vehicle actually starts to enter the scheduled travel route of the own vehicle, thereby avoiding sudden deceleration of the own vehicle.

In the vehicle control method using the vehicle behavior prediction method according to the present embodiment and the vehicle control device using the vehicle behavior prediction device, the index value is less than the first threshold, and the difference between the index value and the first threshold is determined. If the absolute value is equal to or less than a predetermined value, control may be performed to reduce the inter-vehicle distance between the preceding vehicle and the host vehicle. As the inter-vehicle distance between the preceding vehicle and the own vehicle decreases, the probability of entry of the intersecting vehicle decreases, so that it is possible to suppress the possibility that a situation contrary to the prediction result will occur, and to avoid sudden deceleration of the own vehicle.

Further, in the vehicle control method using the vehicle behavior prediction method according to the present embodiment and the vehicle control device using the vehicle behavior prediction device, the index value is equal to or larger than the first threshold, and the difference between the index value and the first threshold is determined. When the absolute value is equal to or less than a predetermined value, control for increasing the inter-vehicle distance between the preceding vehicle and the host vehicle may be performed. As the inter-vehicle distance between the preceding vehicle and the own vehicle increases, the probability of entry of the intersecting vehicle increases, so that the possibility that a situation contrary to the prediction result may occur can be suppressed, and the own vehicle may uselessly enter the intersecting vehicle. Can be avoided.

Although the content of the present invention has been described in connection with the embodiments, the present invention is not limited to the description, and it is obvious to those skilled in the art that various modifications and improvements are possible. The discussion and drawings that form part of this disclosure should not be understood as limiting the invention. From this disclosure, various alternative embodiments, examples, and operation techniques will be apparent to those skilled in the art.

Of course, the present invention includes various embodiments not described herein. Therefore, the technical scope of the present invention is determined only by the invention-specifying matters according to the claims that are appropriate from the above description.

The functions shown in the above embodiments can be implemented by one or a plurality of processing circuits. The processing circuit includes a programmed processing device such as a processing device including an electric circuit. Processors also include devices such as application specific integrated circuits (ASICs) or conventional circuit components arranged to perform the functions described in the embodiments.

DESCRIPTION OF SYMBOLS 21 Object detection part 23 Own vehicle position estimation part 25 Map information acquisition part 50 Vehicle behavior prediction part 51 Intersecting vehicle specification part 53 Leading vehicle specification part 55 Behavior change detection part 57 Threshold change part for behavior prediction 59 Behavior prediction part 70 Vehicle path Generation unit 80 Speed profile generation unit 90 Vehicle control unit 100 Processing unit (controller)

Claims

Detects objects outside the vehicle,
From the object,
Identify an intersecting vehicle having a scheduled travel route that intersects the scheduled travel route of the vehicle,
Identify the preceding vehicle traveling on the scheduled route of the own vehicle,
Detecting a change in behavior of the preceding vehicle,
Setting a first threshold based on the behavior change;
Predicting the entry of the crossing vehicle into the planned travel route of the host vehicle based on the index value indicating the distance between the preceding vehicle and the host vehicle in the planned travel route of the host vehicle and the first threshold value A vehicle behavior prediction method, comprising:
The vehicle behavior prediction method according to claim 1,
A vehicle behavior prediction method, wherein when the index value is equal to or larger than a first threshold value, it is predicted that the crossing vehicle will enter the scheduled travel route of the host vehicle.
The vehicle behavior prediction method according to claim 1 or 2,
A vehicle behavior prediction method, comprising: predicting a time at which the crossing vehicle starts to enter a scheduled travel route of the host vehicle based on the index value and a first threshold value.
A vehicle behavior prediction method according to any one of claims 1 to 3,
Based on the map information, an intersection on the planned traveling route of the own vehicle and an oncoming road opposite to the own vehicle road on which the own vehicle runs is a direction from the oncoming road to the own vehicle road. A method for predicting vehicle behavior, characterized by identifying the intersection that does not have a right / left turn signal indicating whether or not the vehicle can turn in the direction.
The vehicle behavior prediction method according to claim 4,
A vehicle behavior prediction method, wherein a vehicle that is traveling on the opposite road and is scheduled to turn in the one direction at the intersection is specified as the intersection vehicle.
It is a vehicle behavior prediction method according to claim 4 or 5,
A vehicle behavior prediction method, wherein the behavior change of the preceding vehicle is detected based on a preparatory turning operation of the preceding vehicle before entering the intersection.
A vehicle behavior prediction method according to claim 6,
The turning preliminary operation is at least one of a decelerating operation of the preceding vehicle, an operation of moving the preceding vehicle in the one direction in a lane in which the preceding vehicle travels, and an operation of displaying a right / left turn signal of the preceding vehicle. A vehicle behavior prediction method characterized by the above-mentioned.
A vehicle behavior prediction method according to any one of claims 4 to 7,
The time until the preceding vehicle starts entering the intersection is equal to or less than a second threshold value, and
A vehicle behavior predicting method characterized in that the preceding vehicle is specified such that the collision allowance time of the own vehicle with respect to the preceding vehicle is equal to or less than a third threshold value.
A vehicle behavior prediction method according to any one of claims 4 to 8,
A vehicle behavior prediction method, wherein the first threshold value is reduced when a road that the preceding vehicle and the crossing vehicle enter after passing through the intersection is a road having two or more lanes on each side.
A vehicle behavior prediction method according to any one of claims 4 to 9,
The vehicle behavior, wherein the first threshold value is reduced when two or more vehicles scheduled to enter the intersection are waiting behind the traveling direction of the intersection vehicle before entering the intersection. Forecasting method.
A vehicle behavior prediction method according to any one of claims 4 to 10,
A vehicle that reduces the first threshold value when a predetermined number or more of vehicles that are scheduled to enter the intersection are waiting behind the traveling direction of the preceding vehicle before entering the intersection. Behavior prediction method.
A vehicle behavior prediction method according to any one of claims 4 to 11,
If the vehicle that is going to enter the intersection is waiting behind the traveling direction of the intersection vehicle before entering the intersection, and the opposite road is one lane on one side, the first threshold value is reduced. A vehicle behavior predicting method characterized by causing a vehicle behavior to be predicted.
A vehicle behavior prediction method according to any one of claims 4 to 12,
The first threshold value is increased when the road on which the preceding vehicle and the host vehicle travel is composed of two or more lanes on each side excluding the lane on which the vehicle scheduled to turn in the opposite direction travels. A vehicle behavior prediction method characterized by the above-mentioned.
A vehicle behavior prediction method according to any one of claims 1 to 3,
A vehicle behavior prediction method comprising: identifying a merging lane at a merging point with a lane in which the preceding vehicle and the host vehicle travel based on map information.
It is a vehicle behavior prediction method according to claim 14,
A vehicle behavior prediction method, wherein the behavior change of the preceding vehicle is detected based on an acceleration operation of the preceding vehicle before passing through the junction.
It is a vehicle behavior prediction method according to claim 14 or 15,
A vehicle, which is the preceding vehicle before passing the junction, wherein the preceding vehicle whose headway time with respect to the own vehicle when passing the junction is less than or equal to a fourth threshold value is specified. Behavior prediction method.
It is a vehicle behavior prediction method according to claim 14 or 15,
The preceding vehicle before passing the junction, wherein the preceding vehicle whose collision allowance time with respect to the own vehicle when passing the junction is equal to or less than a fourth threshold is specified. Vehicle behavior prediction method.
A vehicle behavior prediction method according to any one of claims 14 to 17,
A vehicle behavior predicting method, wherein a vehicle traveling on the merging lane before passing the merging point is specified as the crossing vehicle.
A vehicle behavior prediction method according to claim 18, wherein:
A vehicle behavior predicting method, wherein the first threshold value is decreased when the intersection vehicle whose time until reaching the merge point is equal to or less than a fifth threshold value does not indicate a merge preparatory operation.
It is a vehicle behavior prediction method according to claim 18 or 19,
A vehicle behavior prediction method, wherein the first threshold value is reduced when the speed of the crossing vehicle is higher than the speed of the host vehicle by a predetermined ratio or more.
A vehicle behavior prediction method according to any one of claims 1 to 3,
A vehicle behavior prediction method characterized by identifying a T-shaped road on a planned traveling route of the vehicle based on map information.
The vehicle behavior prediction method according to claim 21,
Identifying, as the intersecting vehicle, a vehicle that is to enter the T-junction by traveling in a non-priority lane having a lower priority than the lane in which the host vehicle travels among a plurality of roads merging at the T-junction. A vehicle behavior prediction method characterized by the following.
A vehicle behavior prediction method according to claim 21 or 22,
A vehicle behavior prediction method, wherein the behavior change of the preceding vehicle is detected based on a preparatory turning operation of the preceding vehicle before entering the T-shaped road.
A vehicle behavior prediction method according to any one of claims 21 to 23,
The time until the preceding vehicle starts entering the T-shaped intersection is equal to or less than a second threshold value, and
A vehicle behavior predicting method characterized in that the preceding vehicle is specified such that the collision allowance time of the own vehicle with respect to the preceding vehicle is equal to or less than a third threshold value.
A vehicle control method using the vehicle behavior prediction method according to any one of claims 4 to 24,
If the probability of entry of the crossing vehicle into the scheduled travel route of the own vehicle is equal to or greater than the risk level value, before traveling at the intersection of the scheduled travel route of the subject vehicle and the scheduled travel route of the crossed vehicle. A vehicle control method, wherein the vehicle is decelerated.
A vehicle control method using the vehicle behavior prediction method according to any one of claims 4 to 24,
When the index value is less than the first threshold value and the absolute value of the difference between the index value and the first threshold value is equal to or less than a predetermined value, control for reducing the inter-vehicle distance between the preceding vehicle and the host vehicle. A vehicle control method.
A vehicle control method using the vehicle behavior prediction method according to any one of claims 4 to 24,
When the index value is equal to or more than the first threshold value and the absolute value of the difference between the index value and the first threshold value is equal to or less than a predetermined value, a control that increases an inter-vehicle distance between the preceding vehicle and the host vehicle. A vehicle control method.
A sensor for detecting an object outside the vehicle, and a controller,
The controller is
From the object,
Identify an intersecting vehicle having a scheduled travel route that intersects the scheduled travel route of the vehicle,
Identify the preceding vehicle traveling on the scheduled route of the own vehicle,
Detecting a change in behavior of the preceding vehicle,
Setting a first threshold based on the behavior change;
An index value indicating a distance between the preceding vehicle and the own vehicle in the scheduled travel route of the own vehicle and an index value indicating a distance between the preceding vehicle and the first threshold value. A vehicle behavior prediction device characterized by performing prediction.