Other vehicle behavior prediction methods, other vehicle behavior prediction devices, and driving assistance methods

Abstract

The other vehicle behavior prediction method of the present invention calculates the driving path of the vehicle, detects the position of the intersection that exists on the driving path of the vehicle and is within a specified distance from the vehicle, and detects the position of other vehicles around the vehicle before the intersection. When there is a first oncoming vehicle on the road ahead of the driving path of the vehicle after turning right or left at the intersection, the passing area of ​​the vehicle passed by the vehicle when traveling at the intersection and the passing area of ​​other vehicles that the first oncoming vehicle is predicted to pass when traveling at the intersection are calculated, the interval between the passing area of ​​the vehicle and the passing area of ​​other vehicles is calculated, and the distance between the first oncoming vehicle and the intersection is calculated. Based on the interval and the distance, the probability of the first oncoming vehicle traveling at the intersection before the vehicle is predicted.

Description

Technical Field

[0001] The present invention relates to other vehicle behavior prediction methods, other vehicle behavior prediction devices and driving assistance methods. Background Art

[0002] Patent Document 1 describes an intersection yield assistance system that transmits information indicating that a vehicle on a non-priority road has stopped to a driver of a vehicle on a priority road when, in front of an intersection where a non-priority road intersects a priority road, it is determined that the vehicle on the non-priority road has stopped for more than a predetermined time. The intersection yield assistance system transmits information requesting the driver of the vehicle on the priority road to stop in front of the intersection for yielding when the vehicle on the non-priority road has stopped for more than a predetermined time.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Publication No. 2009-251759

[0006] Problems to be solved by the invention

[0007] The intersection yield assistance system described in Patent Document 1 does not transmit information requesting yield to the driver of the vehicle on the priority road when the vehicle on the non-priority road does not stop in front of the intersection for more than a specified time. Therefore, when the host vehicle turns left or right at the intersection, if the oncoming vehicle on the road ahead of the left or right turn does not stop in front of the intersection but moves through the intersection, the host vehicle cannot determine that it should yield the road to the intersection to the oncoming vehicle. As a result, the driver may feel uncomfortable due to the proximity of the host vehicle and the oncoming vehicle. Summary of the invention

[0008] The present invention provides another vehicle behavior prediction method. When the vehicle turns right or left at an intersection, it predicts the probability that the oncoming vehicle on the road ahead of the vehicle will reach the intersection before the vehicle, and can determine whether to give way to the oncoming vehicle when the vehicle turns right or left.

[0009] A behavior prediction method according to one embodiment of the present invention calculates the driving path of the vehicle, detects the position of an intersection that exists on the driving path of the vehicle and is within a specified distance from the vehicle, and detects the position of other vehicles around the vehicle before the intersection. When there is a first oncoming vehicle on the road ahead after the driving path turns right or left at the intersection, the passing area of ​​the vehicle through which the vehicle passes when traveling at the intersection and the passing area of ​​other vehicles that the first oncoming vehicle is predicted to pass when traveling at the intersection are calculated, the interval between the passing area of ​​the vehicle and the passing area of ​​other vehicles is calculated, and the distance between the first oncoming vehicle and the intersection is calculated. Based on the interval and the distance, the probability that the first oncoming vehicle travels at the intersection before the vehicle is predicted is predicted.

[0010] Effects of the Invention

[0011] According to the present invention, when the vehicle turns right or left at an intersection, the probability that an oncoming vehicle on the road ahead of the vehicle will reach the intersection before the vehicle is predicted, and it is possible to determine whether to give way to the oncoming vehicle when the vehicle turns right or left. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a functional block diagram of another vehicle behavior prediction device and a driving assistance device according to an embodiment of the present invention.

[0013] Figure 2A This is a diagram for explaining an example of a scenario to which another vehicle behavior prediction method according to an embodiment of the present invention is applied.

[0014] Figure 2B This is a diagram for explaining an example of a scenario to which another vehicle behavior prediction method according to an embodiment of the present invention is applied.

[0015] Figure 3A This is a diagram for explaining an example of a scenario to which another vehicle behavior prediction method according to an embodiment of the present invention is applied.

[0016] Figure 3B This is a diagram for explaining an example of a scenario to which another vehicle behavior prediction method according to an embodiment of the present invention is applied.

[0017] Figure 4 This is a flowchart showing an example of the operation of another vehicle behavior prediction device and a driving assistance device according to an embodiment of the present invention.

[0018] Figure 5 Yes means Figure 4 A flowchart of an example of detailed steps of step S07.

[0019] Figure 6 This is a diagram for explaining an example of a scenario to which another vehicle behavior prediction method according to the second embodiment of the present invention is applied.

[0020] Figure 7 Yes means Figure 4 A flowchart of an example of detailed steps of step S07. DETAILED DESCRIPTION

[0021] [First embodiment]

[0022] Hereinafter, a first embodiment to which the present invention is applied will be described with reference to the drawings. In the description of the drawings, the same parts are denoted by the same reference numerals and their description will be omitted.

[0023] [Structure of driving assistance device]

[0024] Reference Figure 1 The configuration of the driving assistance device of the present embodiment will be described. The driving assistance device includes an object detection device 1 , a vehicle position estimation device 3 , a map storage device 4 , and a microcomputer 100 .

[0025] The object detection device 1 is equipped with a plurality of different types of object detection sensors such as laser radar, millimeter wave radar, and camera mounted on the vehicle 31 to detect objects around the vehicle 31. The object detection device 1 uses a plurality of object detection sensors to detect objects around the vehicle 31. The object detection device 1 detects, for example, the position, posture, size, speed, etc. of other vehicles, motorcycles, bicycles, pedestrians, obstacles, etc. relative to the vehicle 31. The object detection device 1 outputs, for example, the two-dimensional position, posture, size, speed, etc. of the object in a zenith view (also called a bird's-eye view) observed from the air above the vehicle 31 as a detection result. In addition, when the vehicle 31 and other vehicles or motorcycles around the vehicle are equipped with communication devices that can communicate with each other, the object detection device 1 can also obtain the position, posture, size, speed, etc. of other vehicles or motorcycles around the vehicle by communicating with other vehicles or motorcycles around the vehicle (vehicle-to-vehicle communication).

[0026] The vehicle position estimation device 3 has a position detection sensor such as a GPS (Global Positioning System) or a rangefinder mounted on the vehicle 31 to measure the absolute position of the vehicle 31. The vehicle position estimation device 3 uses the position detection sensor to measure the absolute position of the vehicle 31, that is, the position, posture, and speed of the vehicle 31 relative to a predetermined reference point.

[0027] The map storage device 4 stores map information indicating the structure of the road on which the host vehicle 31 is traveling. The map storage device 4 may have a map database storing the map information, or may obtain the map information from an external map data server through cloud computing. The map information stored in the map storage device 4 includes information on the road structure, such as the absolute positions of the roads and lanes on the roads, the connection relationship of the lanes, and the relative position relationship. In this case, a road refers to a driving area for vehicles including a single lane or multiple lanes with the same driving direction, and a lane refers to a driving area divided by lane markings on the road.

[0028] The microcomputer 100 (an example of a control unit) calculates the driving path of the host vehicle 31 and assists the host vehicle 31 in driving along the calculated driving path. The microcomputer 100 detects the positions of other vehicles around the host vehicle 31, and when there is a first oncoming vehicle 32 on the road ahead after the driving path of the host vehicle 31 turns right or left at an intersection, predicts the behavior of the first oncoming vehicle 32, and controls the driving of the host vehicle 31 based on the result of the predicted behavior of the first oncoming vehicle 32.

[0029] In addition, in the embodiment, the microcomputer 100 is described as an example of a driving assistance device that controls the host vehicle 31. However, the present invention is not limited to this. For example, the microcomputer 100 may also be implemented as another vehicle behavior prediction device that predicts the behavior of the first oncoming vehicle 32. That is, the microcomputer 100 may not calculate the driving path of the host vehicle 31 and control the host vehicle 31 traveling along the driving path, but may finally output a result of predicting the behavior of the first oncoming vehicle 32.

[0030] The microcomputer 100 is a general-purpose microcomputer including a CPU (central processing unit), a memory, and an input / output unit. A computer program (driving assistance program) for functioning as a driving assistance device is installed in the microcomputer 100. By executing the computer program, the microcomputer 100 functions as a plurality of information processing circuits (2, 5, 6, 10, 21) possessed by the driving assistance device. In addition, here, an example of realizing a plurality of information processing circuits (2, 5, 6, 10, 21) possessed by the driving assistance device by software is shown. Of course, dedicated hardware for performing each information processing shown below can also be prepared to constitute the information processing circuit (2, 5, 6, 10, 21). In addition, the plurality of information processing circuits (2, 5, 6, 10, 21) can also be composed of separate hardware. Furthermore, the information processing circuit (2, 5, 6, 10, 21) can also be used as an electronic control unit (ECU) used in other controls related to the vehicle.

[0031] The microcomputer 100 includes: an object detection integration / tracking unit 2, a vehicle position estimation unit 5 in a map, a vehicle path calculation unit 6, a vehicle behavior prediction unit 10, and a vehicle control unit 21 as a plurality of information processing circuits (2, 5, 6, 10, 21). Furthermore, the vehicle behavior prediction unit 10 includes: an intersection detection unit 11, a surrounding vehicle detection unit 12, a passing area interval calculation unit 13, a vehicle intersection distance calculation unit 14, and a vehicle precedence probability prediction unit 15. In addition, when implemented as a vehicle behavior prediction device that predicts the behavior of the first oncoming vehicle 32, the information processing circuit (vehicle control unit 21) is not required.

[0032] The object detection integration / tracking unit 2 integrates the multiple detection results obtained from the multiple object detection sensors of the object detection device 1, and outputs a detection result for each object. Specifically, based on the position, posture, size, and speed of the object obtained from each object detection sensor, the most reasonable position, posture, size, and speed of the object with the smallest error are calculated based on the error characteristics of each object detection sensor. Specifically, by using the known sensor fusion technology, the detection results obtained by multiple sensors are comprehensively evaluated to obtain a more accurate detection result.

[0033] The object detection integration / tracking unit 2 tracks the object detected by the object detection device 1. Specifically, based on the position, posture, size, speed, etc. of the object output at different times, the identity of the object at different times is verified (one-to-one correspondence), and the speed information of the object is estimated based on the one-to-one correspondence. In addition, the position, posture, size, speed, etc. of the object output at different times are stored in the memory in the microcomputer 100, which is used for the detection of other vehicles described later and the calculation of the travel path 51 of other vehicles. In addition, when communication (vehicle-to-vehicle communication) can be performed between the vehicle 31 and other vehicles or motorcycles around the vehicle, it is possible to receive the ID inherent to each vehicle from other vehicles or motorcycles around the vehicle, and verify the identity of the object based on the received ID.

[0034] The in-map vehicle position estimating unit 5 estimates the position and posture of the vehicle 31 on the map based on the absolute position and posture of the vehicle 31 obtained by the vehicle position estimating device 3 and the map data stored in the map storage device 4. Then, the in-map vehicle position estimating unit 5 determines the road on which the vehicle 31 is traveling. In addition, the in-map vehicle position estimating unit 5 may further determine the lane on which the vehicle 31 is traveling.

[0035] The vehicle path calculation unit 6 calculates a road-unit driving path (vehicle driving path 41) of the vehicle 31 from the position of the vehicle 31 on the map obtained by the vehicle position estimation unit 5 to the destination of the vehicle 31 on the map. In addition, the vehicle path calculation unit 6 may also calculate a lane-unit driving path of the vehicle 31.

[0036] The other vehicle behavior prediction unit 10 detects the position of an intersection that exists on the driving path 41 of the vehicle and is within a predetermined distance from the vehicle 31, detects the positions of other vehicles around the vehicle 31 before the intersection, and predicts the probability that the first oncoming vehicle 32 will pass through the intersection before the vehicle 31 when there is a first oncoming vehicle 32 on the road ahead after the driving path 41 of the vehicle turns right or left at the intersection. The other vehicle behavior prediction unit 10 includes: an intersection detection unit 11, a surrounding vehicle detection unit 12, a passing area interval calculation unit 13, an other vehicle intersection distance calculation unit 14, and an other vehicle precedence probability prediction unit 15. The specific structure of the other vehicle behavior prediction unit 10 is described below.

[0037] The intersection detection unit 11 detects the position of an intersection that exists on the vehicle's driving path 41 and within a predetermined distance from the current position of the vehicle 31 based on the information of the vehicle's driving path 41 obtained by the vehicle's path calculation unit 6. The intersection detection unit 11 determines whether the vehicle's driving path 41 turns right or left at the intersection.

[0038] The surrounding vehicle detection unit 12 detects the positions of other vehicles around the host vehicle 31 before the intersection detected by the intersection detection unit 11. Specifically, when the host vehicle's driving path 41 turns right or left at the intersection detected by the intersection detection unit 11, the surrounding vehicle detection unit 12 obtains information on the detection result obtained by the object detection integration / tracking unit 2 before the intersection. Then, based on the position, posture, size, and speed of the object obtained, it is determined whether the object is another vehicle. The surrounding vehicle detection unit 12 determines the positions of other vehicles on the map based on the positions of other vehicles existing around the host vehicle 31 and the position of the host vehicle 31 on the map. Then, the surrounding vehicle detection unit 12 determines whether there is a first oncoming vehicle 32 on the road ahead after the host vehicle's driving path 41 turns right or left at the intersection.

[0039] When there is a first oncoming vehicle 32 on the road ahead after the host vehicle driving path 41 turns right or left at the intersection, the passing area interval calculation unit 13 predicts the action intention of the first oncoming vehicle 32 based on the position, posture, speed and road structure of the first oncoming vehicle 32, and calculates the driving path of the first oncoming vehicle 32 at the intersection (the other vehicle driving path 51). Then, the host vehicle passing area 42 that the host vehicle 31 passes when traveling at the intersection and the other vehicle passing area 52 that the first oncoming vehicle 32 is predicted to pass when traveling at the intersection are calculated, and the interval between the host vehicle passing area 42 and the other vehicle passing area 52 is calculated.

[0040] Specifically, the passing area interval calculation unit 13 calculates the area through which the host vehicle 31 passes when the host vehicle 31 travels on the host vehicle travel path 41 turning right or left at the intersection, that is, the host vehicle passing area 42, based on the road structure of the intersection on the map, the host vehicle travel path 41, and the vehicle width of the host vehicle 31. Furthermore, the passing area interval calculation unit 13 calculates the area through which the first oncoming vehicle 32 is predicted to pass when the first oncoming vehicle 32 travels along the other vehicle travel path 51 at the intersection, that is, the other vehicle passing area 52, based on the road structure of the intersection on the map, the other vehicle travel path 51, and the size (vehicle width) of the first oncoming vehicle 32. Then, the passing area interval calculation unit 13 calculates the closest interval between the host vehicle passing area 42 and the other vehicle passing area 52 as the interval 61 between the host vehicle passing area 42 and the other vehicle passing area 52.

[0041] When the first oncoming vehicle 32 exists on the road ahead after the host vehicle driving path 41 turns right or left at the intersection, the other vehicle intersection distance calculation unit 14 calculates the distance 71 between the first oncoming vehicle 32 and the intersection. The other vehicle intersection distance calculation unit 14 calculates the distance 71 between the first oncoming vehicle 32 and the intersection based on the position of the first oncoming vehicle 32 on the map and the road structure of the intersection on the map. The other vehicle intersection distance calculation unit 14 calculates the distance 71 between the first oncoming vehicle 32 and the intersection, for example, based on the distance between the first oncoming vehicle 32 and the center of the intersection. In addition, the other vehicle intersection distance calculation unit 14 may detect the position of the stop line in front of the intersection, and calculate the distance 71 between the first oncoming vehicle 32 and the intersection based on the distance between the first oncoming vehicle 32 and the stop line. In this case, the other vehicle intersection distance calculation unit 14 may also calculate the distance 71 between the first oncoming vehicle 32 and the intersection by subtracting the distance between the first oncoming vehicle 32 and the stop line from the distance between the stop line and the center of the intersection. In addition, the position of the crosswalk before the intersection and the position of the curb at the entrance of the intersection may be detected instead of the stop line before the intersection, and the calculation method of the distance 71 between the first oncoming vehicle 32 and the intersection is not particularly limited.

[0042] The other vehicle precedence probability prediction unit 15 predicts the probability that the first oncoming vehicle 32 will arrive at the intersection before the host vehicle 31 based on the interval 61 between the host vehicle passing area 42 and the other vehicle passing area 52, and the distance 71 between the first oncoming vehicle 32 and the intersection. When the interval 61 is less than a predetermined interval value, and the distance 71 is less than a predetermined distance value, the other vehicle precedence probability prediction unit 15 predicts that the probability that the first oncoming vehicle 32 will arrive at the intersection before the host vehicle 31 is higher than the probability that the host vehicle 31 will arrive at the intersection before the first oncoming vehicle 32. Figure 2A to Figure 2B as well as Figure 3A to Figure 3B , an example of the other vehicle behavior prediction method performed by the other vehicle prior probability prediction unit 15 is described.

[0043] [Other vehicle behavior prediction methods]

[0044] exist Figure 2A and Figure 2B In FIG. 4 , the vehicle 31's own driving path 41 turns left at the intersection, and there is a first oncoming vehicle 32 on the road ahead after the vehicle's driving path 41 turns left. Figure 2AIn the figure, the interval 61 between the host vehicle passing area 42 and the other vehicle passing area 52 is narrow, and the first oncoming vehicle 32 is located near the intersection. Therefore, if the host vehicle 31 directly travels at the intersection, the first oncoming vehicle 32 travels at the intersection before the host vehicle 31 or at the same time as the host vehicle 31, and it is possible that the host vehicle 31 and the first oncoming vehicle 32 are close to each other.

[0045] On the other hand, Figure 2B In, with Figure 2A Similarly, the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is narrow. Figure 2A Therefore, even if the host vehicle 31 directly travels at the intersection, it can be predicted that the first oncoming vehicle 32 will travel at the intersection after the host vehicle 31, and the possibility that the host vehicle 31 and the first oncoming vehicle 32 are close to each other is low.

[0046] Therefore, when the condition that the interval 61 between the host vehicle passing area 42 and the other vehicle passing area 52 is less than a predetermined interval value (hereinafter referred to as condition 1) and the condition that the distance 71 between the first oncoming vehicle 32 and the intersection is less than a predetermined distance value (hereinafter referred to as condition 2) are both satisfied, the other vehicle precedence probability prediction unit 15 predicts that the probability of the first oncoming vehicle 32 traveling at the intersection before the host vehicle 31 is high. Moreover, when at least one of the condition 1 or the condition 2 is not satisfied, the probability of the first oncoming vehicle 32 traveling at the intersection before the host vehicle 31 is predicted to be low.

[0047] For example, in Figure 2A , the other vehicle precedence probability prediction unit 15 determines that the interval 61 between the host vehicle passing area 42 and the other vehicle passing area 52 is less than the predetermined interval value, and determines that the distance 71 between the first oncoming vehicle 32 and the intersection is less than the predetermined distance value. In this case, since both conditions 1 and 2 are satisfied, the other vehicle precedence probability prediction unit 15 predicts that the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 is high.

[0048] On the other hand, Figure 2B , the other vehicle precedence probability prediction unit 15 determines that the interval 61 between the host vehicle passing area 42 and the other vehicle passing area 52 is less than the predetermined interval value, and determines that the distance 71 between the first oncoming vehicle 32 and the intersection is greater than the predetermined distance value. In this case, since condition 1 is satisfied but condition 2 is not satisfied, the other vehicle precedence probability prediction unit 15 predicts that the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 is low.

[0049] In addition, Figure 3A and Figure 3B In FIG. 4 , the vehicle driving path 41 of the vehicle 31 turns right at the intersection, and there is a first oncoming vehicle 32 on the road ahead after the right turn. Figure 3A In, with Figure 2A Similarly, the other-vehicle precedence probability prediction unit 15 determines that the condition 1 and the condition 2 are satisfied. Then, it is predicted that the probability that the first oncoming vehicle 32 will travel through the intersection before the host vehicle 31 is high.

[0050] On the other hand, Figure 3B In, with Figure 2B Similarly, the other-vehicle precedence probability prediction unit 15 determines that condition 1 is satisfied but condition 2 is not satisfied. Then, it is predicted that the probability that the first oncoming vehicle 32 will travel through the intersection before the host vehicle 31 is low.

[0051] The vehicle control unit 21 controls the travel of the host vehicle 31 based on the result of the prediction of the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 by the other vehicle behavior prediction unit 10. When the other vehicle precedence probability prediction unit 15 predicts that the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 is higher than the probability that the host vehicle 31 will travel at the intersection before the first oncoming vehicle 32, the vehicle control unit 21 controls the actuator of the host vehicle 31 to stop before the intersection and yield the travel at the intersection to the first oncoming vehicle 32. When the other vehicle precedence probability prediction unit 15 predicts that the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 is lower than the probability that the host vehicle 31 will travel at the intersection before the first oncoming vehicle 32, the vehicle control unit 21 controls the actuator of the host vehicle 31 to travel at the intersection without yielding the travel at the intersection to the first oncoming vehicle 32.

[0052] In addition, when the vehicle driving path 41 does not turn right or left at the intersection, when the first oncoming vehicle 32 does not exist on the road ahead after the vehicle driving path 41 turns right or left, the other vehicle behavior prediction unit 10 ends the process. Figure 5 In the case of the processing of, the vehicle control unit 21 controls the actuator of the host vehicle 31 so that it directly travels at the intersection along the host vehicle travel path 41. In addition, the actuator includes a brake actuator, an accelerator actuator, a steering actuator, and the like.

[0053] [Driver assistance processing sequence]

[0054] Next, refer to Figure 4 and Figure 5 The flowchart of FIG. 1 illustrates an example of the sequence of driving assistance processing using the driving assistance device of the present embodiment. Figure 1The microcomputer 100 is used as another vehicle behavior prediction device to predict the action of the first oncoming vehicle 32, and can be used as the final output Figure 4 The other vehicle behavior prediction processing is implemented based on the result of the processing action shown in step S07.

[0055] First, in Figure 4 In step S01, the object detection device 1 uses multiple object detection sensors to detect the behavior of objects around the vehicle 31. Entering step S02, the object detection integration / tracking unit 2 integrates multiple detection results obtained from multiple object detection sensors and outputs a detection result for each object. Then, each object detected and integrated is tracked.

[0056] In step S03, the vehicle position estimation device 3 uses the position detection sensor to measure the position, posture and speed of the vehicle 31 relative to a predetermined reference point. In step S04, the map storage device 4 acquires map information indicating the structure of the road on which the vehicle 31 travels.

[0057] Proceeding to step S05 , the on-map vehicle position estimating unit 5 estimates the position and posture of the on-map vehicle 31 based on the position of the on-map vehicle 31 measured in step S03 and the map data acquired in step S04 .

[0058] Proceeding to step S06 , the vehicle path calculation unit 6 calculates a road unit driving path (vehicle driving path 41 ) of the vehicle 31 from the position of the vehicle 31 on the map obtained by the vehicle position estimation unit 5 to the destination of the vehicle 31 on the map.

[0059] Entering step S07, the other vehicle behavior prediction unit 10 detects the position of the intersection that exists on the vehicle's driving path 41 and is within a specified distance from the vehicle 31, and detects the positions of other vehicles around the vehicle 31 before the intersection. If there is a first oncoming vehicle 32 on the road ahead after the vehicle's driving path 41 turns right or left at the intersection, the probability of the first oncoming vehicle 32 traveling at the intersection before the vehicle 31 is predicted. Figure 5 The details of step S07 are described.

[0060] First, in step S701, the intersection detection unit 11 detects the position of an intersection that exists on the vehicle's driving path 41 and is within a specified distance from the current position of the vehicle 31 based on the information of the vehicle's driving path 41 obtained by the vehicle's path calculation unit 6. The intersection detection unit 11 determines whether the vehicle's driving path 41 turns right or left at the intersection. In the case where the vehicle's driving path 41 turns right or left at the intersection ("Yes" in step S702), the processing enters step S703. On the other hand, in the case where the vehicle's driving path 41 does not turn right or left at the intersection ("No" in step S702), the other vehicle behavior prediction unit 10 ends. Figure 5 Therefore, Figure 4 Step S07 ends.

[0061] In step S703, the surrounding vehicle detection unit 12 detects the positions of other vehicles around the vehicle in front of the intersection detected by the intersection detection unit 11. The process proceeds to step S704, and the surrounding vehicle detection unit 12 determines whether there is a first oncoming vehicle 32 on the road ahead after the vehicle's driving path 41 turns right or left at the intersection. If there is a first oncoming vehicle 32 on the road ahead after turning right or left at the intersection ("Yes" in step S704), the process proceeds to step S705. On the other hand, if there is no first oncoming vehicle 32 on the road ahead after turning right or left at the intersection ("No" in step S704), the other vehicle behavior prediction unit 10 ends. Figure 5 Therefore, Figure 4 Step S07 ends.

[0062] In step S705, the area interval calculation unit 13 predicts the action intention of the first oncoming vehicle 32 based on the position, posture, speed and road structure of the first oncoming vehicle 32, and calculates the other vehicle driving path 51 at the intersection. The area interval calculation unit 13 calculates the own vehicle passing area 42 based on the road structure of the intersection on the map, the own vehicle driving path 41, and the vehicle width of the own vehicle 31. The processing proceeds to step S706, and the area interval calculation unit 13 calculates the other vehicle passing area 52 based on the road structure of the intersection on the map, the other vehicle driving path 51, and the size (vehicle width) of the first oncoming vehicle 32. The processing proceeds to step S707, and the area interval calculation unit 13 calculates the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52.

[0063] The process proceeds to step S708 , where the other-vehicle intersection distance calculation unit 14 calculates the distance 71 between the first oncoming vehicle 32 and the intersection based on the position of the first oncoming vehicle 32 on the map and the road structure of the intersection on the map.

[0064] The process proceeds to step S709, and the other vehicle advance probability prediction unit 15 determines whether the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is less than the predetermined value of the interval. If the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is less than the predetermined value of the interval ("Yes" in step S709), the process proceeds to step S710. On the other hand, if the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is greater than the predetermined value of the interval ("No" in step S709), the process proceeds to step S712.

[0065] In step S710, the other vehicle precedence probability prediction unit 15 determines whether the distance 71 between the intersection and the first oncoming vehicle 32 is less than a predetermined distance value. If the distance 71 between the intersection and the first oncoming vehicle 32 is less than the predetermined distance value ("Yes" in step S710), the process proceeds to step S711. On the other hand, if the distance 71 between the intersection and the first oncoming vehicle 32 is greater than the predetermined distance value ("No" in step S710), the process proceeds to step S711.

[0066] In step S711, the other vehicle precedence probability prediction unit 15 predicts that the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 is higher than the probability that the host vehicle 31 will travel at the intersection before the first oncoming vehicle 32, and the process ends. Figure 5 In step S712, the other vehicle precedence probability prediction unit 15 predicts that the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 is lower than the probability that the host vehicle 31 will travel at the intersection before the first oncoming vehicle 32, and the process ends. Figure 5 Therefore, Figure 4 Step S07 ends.

[0067] Enter Figure 4 In step S08, the vehicle control unit 21 controls the travel of the host vehicle 31 based on the result of the prediction of the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 by the other vehicle behavior prediction unit 10. In addition, in the case where the host vehicle's travel path 41 does not turn right or left at the intersection, or the first oncoming vehicle 32 does not exist on the road ahead after the host vehicle's travel path 41 turns right or left, the other vehicle behavior prediction unit 10 ends the process midway. Figure 5 In the case of the processing, the vehicle control unit 21 controls the actuator of the host vehicle 31 so that it travels directly at the intersection along the host vehicle travel path 41.

[0068] In addition, the passing area interval calculation unit 13 may also calculate the right turn, left turn, straight driving, etc. of the first oncoming vehicle 32 at the intersection, all other vehicle travel paths and other vehicle passing areas that the first oncoming vehicle 32 may travel, and calculate the intervals between the own vehicle passing area 42 and each of the plurality of other vehicle passing areas based on the position, posture, speed and road structure of the first oncoming vehicle 32. In this case, the other vehicle prior probability prediction unit 15 may also determine whether any of the intervals between the own vehicle passing area 42 and each of the plurality of other vehicle passing areas is less than a predetermined value of the interval set in advance.

[0069] [Effects of the First Embodiment]

[0070] As described above, according to this embodiment, the following effects can be obtained.

[0071] The other vehicle behavior prediction method of this embodiment calculates the driving path of the vehicle, detects the position of the intersection that exists on the driving path of the vehicle and within a specified distance from the vehicle, and detects the position of other vehicles around the vehicle before the intersection. When there is a first oncoming vehicle on the road ahead of the driving path of the vehicle after turning right or left at the intersection, the passing area of ​​the vehicle through which the vehicle passes when traveling at the intersection and the passing area of ​​other vehicles that the first oncoming vehicle is predicted to pass when traveling at the intersection are calculated, the interval between the passing area of ​​the vehicle and the passing area of ​​other vehicles is calculated, and the distance between the first oncoming vehicle and the intersection is calculated. Then, based on the interval and the distance, the probability that the first oncoming vehicle travels at the intersection before the vehicle is predicted.

[0072] Thus, when the vehicle turns right or left at an intersection, the probability that the oncoming vehicle will advance to the intersection before the vehicle is predicted based on the interval between the area through which the vehicle passes and other areas through which other vehicles pass, and the distance between the oncoming vehicle and the intersection on the road ahead of the right or left turn, and whether the vehicle will yield the passage to the intersection to the oncoming vehicle is determined, thereby enabling the vehicle's driving assistance to be implemented. As a result, it is possible to prevent the vehicle from approaching the oncoming vehicle when turning left or right at the intersection, thereby preventing the driver of the vehicle from feeling uncomfortable. In addition, by yielding the passage of the vehicle to the intersection to the oncoming vehicle, the time required for the oncoming vehicle to pass through the intersection can be shortened. In the case where the vehicle does not have to yield the passage to the intersection to the oncoming vehicle, the vehicle can smoothly advance to the intersection, and the time required for the vehicle to pass through the intersection can be shortened.

[0073] In addition, in the other vehicle behavior prediction methods of the present embodiment, when the interval between the area through which the vehicle passes and the area through which other vehicles pass is less than a predetermined interval value, and the distance between the first oncoming vehicle and the intersection is less than a predetermined distance value, the probability that the first oncoming vehicle will travel at the intersection before the vehicle is higher than the probability that the vehicle will travel at the intersection before the first oncoming vehicle. Thus, when the interval between the area through which the vehicle passes and the area through which other vehicles pass is less than a predetermined value, and the distance between the first oncoming vehicle and the intersection is less than a predetermined value, it is determined that the movement to the intersection is yielded to the first oncoming vehicle, thereby enabling the driving assistance of the vehicle. In addition, when the interval between the area through which the vehicle passes and the area through which other vehicles pass is greater than a predetermined value, or the distance between the first oncoming vehicle and the intersection is greater than a predetermined value, it is determined that the movement to the intersection is not yielded to the first oncoming vehicle, thereby enabling the driving assistance of the vehicle.

[0074] In addition, the other vehicle behavior prediction method of the present embodiment calculates the distance between the first oncoming vehicle and the intersection based on the distance between the first oncoming vehicle and the center of the intersection. Alternatively, the other vehicle behavior prediction method of the driving assistance device of the present embodiment can also detect the position of the stop line in front of the intersection, and calculate the distance between the first oncoming vehicle and the intersection based on the distance between the first oncoming vehicle and the stop line.

[0075] In addition, the driving assistance method using the other vehicle behavior prediction method of the present embodiment controls the travel of the host vehicle based on the result of predicting the probability that the first oncoming vehicle will travel at the intersection before the host vehicle. Thus, when the probability that the first oncoming vehicle will travel at the intersection before the host vehicle is high, the travel of the host vehicle can be controlled so that the travel to the intersection is yielded to the first oncoming vehicle.

[0076] Furthermore, in another vehicle behavior prediction method of the present embodiment, when the priority of the road before the driving path of the present vehicle turns right or left at the intersection is higher than the priority of the road ahead after the driving path of the present vehicle turns right or left, the probability that the first oncoming vehicle will travel to the intersection before the present vehicle can be predicted based on the interval and distance. When the priority of the present vehicle is that the priority of the first oncoming vehicle is high, by predicting the probability that the first oncoming vehicle will travel to the intersection before the present vehicle, even if the first oncoming vehicle travels to the intersection before the present vehicle despite the high priority of the present vehicle, it is possible to judge the first oncoming vehicle to give way to the first oncoming vehicle based on the behavior of the first oncoming vehicle. As a result, it is possible to prevent the present vehicle from getting close to the first oncoming vehicle when turning left or right at the intersection, causing discomfort to the driver of the present vehicle.

[0077] [Second Embodiment]

[0078] Hereinafter, a second embodiment to which the present invention is applied will be described with reference to the drawings. In the description of the drawings, the same reference numerals are given to the same parts as those of the first embodiment, and the description thereof will be omitted.

[0079] The other vehicle precedence probability prediction unit 15 of the driving assistance device of the first embodiment predicts that the probability of the first oncoming vehicle 32 traveling at the intersection before the host vehicle 31 is high when both the condition 1 that the interval 61 between the host vehicle passing area 42 and the other vehicle passing area 52 is less than the prescribed value of the interval and the condition 2 that the distance 71 between the first oncoming vehicle 32 and the intersection is less than the prescribed value of the distance are satisfied. Then, the vehicle control unit 21 controls the travel of the host vehicle 31 based on the prediction result.

[0080] In contrast, the other vehicle advance probability prediction unit 15 of the driving assistance device of the second embodiment adds the probability that the first oncoming vehicle 32 travels at the intersection before the host vehicle 31 (hereinafter referred to as the other vehicle advance probability) when the above-mentioned two conditions, condition 1 and condition 2, are satisfied. Furthermore, the other vehicle advance probability prediction unit 15 may further set a condition that is different from condition 1 and condition 2 and affects the other vehicle advance probability. In this case, the other vehicle advance probability prediction unit 15 adds the other vehicle advance probability when a condition different from condition 1 and condition 2 is satisfied. Then, the other vehicle advance probability prediction unit 15 determines the control method of the host vehicle 31 corresponding to the value of the other vehicle advance probability at the moment when the judgment of all conditions ends. In addition, the other vehicle advance probability prediction unit 15 may also determine the control method of the host vehicle 31 based on the combination of conditions determined to be satisfied, rather than the value of the other vehicle advance probability.

[0081] Then, the vehicle control unit 21 controls the travel of the host vehicle 31 based on the determination result of the other-vehicle preceding probability prediction unit 15. The configuration of other driving support devices is the same as that of the first embodiment, and thus the description thereof is omitted.

[0082] [Other vehicle behavior prediction methods]

[0083] Below, refer to Figure 6 , an example of another vehicle behavior prediction method of the driving assistance device of the second embodiment is described. Figure 6 In the figure, the vehicle driving path 41 of the vehicle 31 turns left at the intersection, and there is a first oncoming vehicle 32 on the road ahead after the vehicle driving path 41 turns left. In addition, there is a second oncoming vehicle 33 approaching the intersection on the road before the vehicle driving path 41 turns left at the intersection, and the second oncoming vehicle 33 stops in front of the intersection.

[0084] exist Figure 6 In the example, the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is narrow, and the first oncoming vehicle 32 is located near the intersection. The other vehicle prior probability prediction unit 15, for example, adds the other vehicle prior probability when conditions 1 and 2 are satisfied. The other vehicle prior probability prediction unit 15, for example, adds 60% to the other vehicle prior probability.

[0085] In addition, Figure 6 In the example, there is a second oncoming vehicle 33 approaching the intersection on the road before the host vehicle's driving path 41 turns left at the intersection, so the first oncoming vehicle 32 may slow down or temporarily stop. In contrast, in the case where there is no second oncoming vehicle 33 approaching the intersection on the road before the host vehicle's driving path 41 turns left at the intersection, since there is no obstacle for the first oncoming vehicle 32 to travel at the intersection, it can be predicted that the probability that the first oncoming vehicle 32 will travel at the intersection before the host vehicle 31 is further increased. Therefore, the other vehicle priority probability prediction unit 15 adds the other vehicle priority probability when the condition (hereinafter referred to as condition 3) that there is no second oncoming vehicle 33 approaching the intersection on the road before the host vehicle's driving path 41 turns left at the intersection is met. For example, when condition 3 is met, the other vehicle priority probability prediction unit 15 adds 10% to the other vehicle priority probability.

[0086] Furthermore, the second oncoming vehicle 33 stops in front of the intersection. Therefore, it can be predicted that there is no obstacle for the first oncoming vehicle 32 to travel at the intersection, and the probability that the first oncoming vehicle 32 travels at the intersection before the host vehicle 31 is further increased. Therefore, the other vehicle precedence probability prediction unit 15 adds the other vehicle precedence probability when the condition (hereinafter referred to as condition 4) that there is a second oncoming vehicle 33 approaching the intersection on the road before the host vehicle's driving path 41 turns left at the intersection and the second oncoming vehicle 33 stops in front of the intersection is met. For example, when condition 4 is met, the other vehicle precedence probability prediction unit 15 adds 10% to the other vehicle precedence probability.

[0087] In addition, as another condition, when the speed of the first oncoming vehicle 32 is fast, it is considered that the possibility that the first oncoming vehicle intends to stop in front of the intersection is low, and it can be predicted that the probability that the first oncoming vehicle travels at the intersection before the host vehicle is further increased. Therefore, when the condition (hereinafter referred to as condition 5) that the speed of the first oncoming vehicle 32 is greater than the predetermined value of the speed set in advance is satisfied, the other vehicle precedence probability prediction unit 15 adds the other vehicle precedence probability. For example, when condition 5 is satisfied, the other vehicle precedence probability prediction unit 15 adds 10% to the other vehicle precedence probability.

[0088] The other vehicle preceding probability prediction unit 15 determines a control method corresponding to the other vehicle preceding probability at the time when the determination of conditions 1 to 5 is completed. For example, the other vehicle preceding probability prediction unit 15 determines to start decelerating the host vehicle 31 when the other vehicle preceding probability is greater than or equal to a first predetermined value and less than a second predetermined value.

[0089] For example, when the other-vehicle precedence probability is 60% or more and less than 70%, the other-vehicle precedence probability prediction unit 15 determines to start decelerating the host vehicle 31 .

[0090] When the other vehicle precedence probability is greater than or equal to the second predetermined value and less than the third predetermined value, the host vehicle 31 is judged to slow down. For example, when the other vehicle precedence probability is greater than or equal to 70% and less than 80%, the host vehicle 31 is judged to slow down.

[0091] Then, when the other vehicle's leading probability is greater than or equal to the third predetermined value, it is determined that the host vehicle 31 is stopped in front of the intersection. For example, when the other vehicle's leading probability prediction unit 15 is greater than or equal to 80%, it is determined that the host vehicle 31 is stopped in front of the intersection. The vehicle control unit 21 controls the travel of the host vehicle 31 based on the determination result of the other vehicle's leading probability prediction unit 15.

[0092] Next, refer to Figure 7 An example of a driving assistance process of the driving assistance device of the second embodiment is described. The driving assistance device of this embodiment performs the following steps. Figure 4 The same process is performed as in step S01 to step S06. Figure 4 In step S07, Figure 5 After the same processing as steps S701 to S708, Figure 7 In the driving assistance process of the second embodiment, description of the same processes as those of the first embodiment will be omitted.

[0093] exist Figure 7 In step S720, the other vehicle advance probability prediction unit 15 determines whether the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is less than the predetermined value of the interval. When the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is less than the predetermined value of the interval ("Yes" in step S720), the process proceeds to step S721. On the other hand, when the interval 61 between the own vehicle passing area 42 and the other vehicle passing area 52 is greater than the predetermined value of the interval ("No" in step S720), the process proceeds to step S723.

[0094] In step S721, the other vehicle precedence probability prediction unit 15 determines whether the distance 71 between the intersection and the first oncoming vehicle 32 is less than a predetermined distance value. If the distance 71 between the intersection and the first oncoming vehicle 32 is less than the predetermined distance value ("Yes" in step S721), the process proceeds to step S722. On the other hand, if the distance 71 between the intersection and the first oncoming vehicle 32 is greater than the predetermined distance value ("No" in step S721), the process proceeds to step S723.

[0095] In step S722, the other vehicle precedence probability prediction unit 15 adds the other vehicle precedence probability. For example, the other vehicle precedence probability prediction unit 15 adds 60% to the initial value 0% of the other vehicle precedence probability. Then, the process proceeds to step S723.

[0096] In step S723, the other vehicle precedence probability prediction unit 15 determines whether there is a second oncoming vehicle 33 approaching the intersection on the road before the vehicle's driving path 41 turns right or left at the intersection. If there is a second oncoming vehicle 33 approaching the intersection on the road before the vehicle's driving path 41 turns right or left at the intersection ("Yes" in step S723), the process proceeds to step S725. On the other hand, if there is no second oncoming vehicle 33 approaching the intersection on the road before the vehicle's driving path 41 turns right or left at the intersection ("No" in step S723), the process proceeds to step S724.

[0097] In step S724, the other vehicle precedence probability prediction unit 15 adds the other vehicle precedence probability. The other vehicle precedence probability prediction unit 15 adds, for example, 10% to the other vehicle precedence probability. Then, the process proceeds to step S727.

[0098] In step S725, the other vehicle precedence probability prediction unit 15 determines whether the second oncoming vehicle 33 stops before the intersection. If the second oncoming vehicle 33 stops before the intersection ("Yes" in step S725), the process proceeds to step S726. On the other hand, if the second oncoming vehicle 33 does not stop before the intersection ("No" in step S725), the process proceeds to step S727.

[0099] In step S726, the other vehicle precedence probability prediction unit 15 adds the other vehicle precedence probability. The other vehicle precedence probability prediction unit 15 adds, for example, 10% to the other vehicle precedence probability. Then, the process proceeds to step S727.

[0100] In step S727, the other vehicle precedence probability prediction unit 15 determines whether the speed of the first oncoming vehicle 32 is greater than the predetermined speed value. If the speed of the first oncoming vehicle 32 is greater than the predetermined speed value ("Yes" in step S727), the process proceeds to step S728. On the other hand, if the speed of the first oncoming vehicle 32 is less than the predetermined speed value ("No" in step S727), the process proceeds to step S729.

[0101] In step S728, the other vehicle precedence probability prediction unit 15 adds the other vehicle precedence probability. The other vehicle precedence probability prediction unit 15 adds, for example, 10% to the other vehicle precedence probability. Then, the process proceeds to step S729.

[0102] In step S729, the other vehicle prior probability prediction unit 15 determines the control method of the host vehicle 31 corresponding to the value of the other vehicle prior probability. For example, when the other vehicle prior probability is greater than 60% and less than 70%, the other vehicle prior probability prediction unit 15 determines to start decelerating the host vehicle 31. When the other vehicle prior probability is greater than 70% and less than 80%, the host vehicle 31 is determined to slow down. When the other vehicle prior probability is greater than 80%, the host vehicle 31 is determined to stop in front of the intersection. Then, end Figure 7 Processing, end Figure 4 Step S07.

[0103] Processing Entry Figure 4 In step S08 , the vehicle control unit 21 controls the travel of the host vehicle 31 based on the determination result of the other vehicle preceding probability prediction unit 15 .

[0104] [Effects of the Second Embodiment]

[0105] As described above, according to this embodiment, the following effects can be obtained.

[0106] In another vehicle behavior prediction method of this embodiment, when there is no second oncoming vehicle approaching the intersection on the road before the driving path of the vehicle turns right or left at the intersection, the probability that the first oncoming vehicle will travel at the intersection before the vehicle is added. When there is no second oncoming vehicle on the road before the driving path of the vehicle turns right or left at the intersection, since there is no obstacle when the first oncoming vehicle travels at the intersection, it is possible to predict that the probability that the first oncoming vehicle will travel at the intersection before the vehicle is further improved. Thus, the probability that the first oncoming vehicle will travel at the intersection before the vehicle can be more accurately predicted.

[0107] In addition, in another vehicle behavior prediction method of the present embodiment, when there is a second oncoming vehicle approaching the intersection on the road before the driving path of the present vehicle turns right or left at the intersection, and the second oncoming vehicle stops in front of the intersection, the probability that the first oncoming vehicle will travel to the intersection before the present vehicle is added. When there is a second oncoming vehicle on the road before the driving path of the present vehicle turns left or right at the intersection, and the second oncoming vehicle stops in front of the intersection, since the obstacles for other vehicles to travel at the intersection disappear, it is possible to predict that the probability that the first oncoming vehicle will travel to the intersection before the present vehicle is further increased. As a result, the probability that the first oncoming vehicle will travel to the intersection before the present vehicle can be more accurately predicted.

[0108] In another vehicle behavior prediction method of this embodiment, when the speed of the first oncoming vehicle is greater than a predetermined speed value, the probability that the first oncoming vehicle will travel to the intersection before the host vehicle is added. When the speed of the first oncoming vehicle is fast, it is considered that the possibility that the first oncoming vehicle intends to stop in front of the intersection is low, and the probability that the first oncoming vehicle will travel to the intersection before the host vehicle can be predicted to be further increased. In this way, the probability that the first oncoming vehicle will travel to the intersection before the host vehicle can be more accurately predicted.

[0109] The driving assistance method using the other vehicle behavior prediction method of the present embodiment starts decelerating the vehicle when the probability that the first oncoming vehicle travels at the intersection before the vehicle is greater than the first specified value and less than the second specified value. When the probability that the first oncoming vehicle travels at the intersection before the vehicle is greater than the first specified value and less than the second specified value, the vehicle can start decelerating, and the first oncoming vehicle can be prevented from approaching the vehicle when traveling to the intersection. The risk of the first oncoming vehicle approaching the vehicle can be reduced.

[0110] The driving assistance method using the other vehicle behavior prediction method of the present embodiment slows down the host vehicle when the probability that the first oncoming vehicle travels at the intersection before the host vehicle is greater than the second specified value and less than the third specified value. When the probability that the first oncoming vehicle travels at the intersection before the host vehicle is greater than the second specified value and less than the third specified value, the host vehicle can be slowed down, and the first oncoming vehicle can be prevented from approaching the host vehicle when traveling to the intersection. The risk of the first oncoming vehicle approaching the host vehicle can be reduced.

[0111] The driving assistance method using the other vehicle behavior prediction method of the present embodiment stops the host vehicle in front of the intersection when the probability that the first oncoming vehicle will travel to the intersection before the host vehicle is greater than a third predetermined value. When the probability that the first oncoming vehicle will travel to the intersection before the host vehicle is greater than a third predetermined value, the host vehicle can be stopped in front of the intersection, and the first oncoming vehicle and the host vehicle can be prevented from approaching each other when traveling to the intersection.

[0112] Explanation of symbols

[0113] 31: This vehicle

[0114] 41: The driving path of the vehicle

[0115] 100: Microcomputer (driving assistance device)

[0116] 32: First oncoming vehicle

[0117] 42: The vehicle passes through the area

[0118] 52: Other vehicles passing through the area

[0119] 61: Interval

[0120] 71: Distance

Claims

1. A method for predicting the behavior of other vehicles around a vehicle, wherein the method predicts the behavior of other vehicles around the vehicle, wherein: Calculate the vehicle's driving path. detecting a position of an intersection that is on a travel path of the host vehicle and within a predetermined distance from the host vehicle, Before the intersection, detecting the positions of other vehicles around the host vehicle, When there is a first oncoming vehicle on the road ahead after the driving path of the host vehicle turns right or left at the intersection, calculating a vehicle passing area through which the host vehicle passes when traveling at the intersection and other vehicle passing areas through which the first oncoming vehicle is predicted to pass when traveling at the intersection, The shortest distance between the own vehicle passing area and the other vehicle passing area is calculated as the distance between the own vehicle passing area and the other vehicle passing area, calculating the distance between the first oncoming vehicle and the intersection, When the interval is smaller than a predetermined value of the interval and the distance is smaller than a predetermined value of the distance, the probability that the first oncoming vehicle travels at the intersection before the host vehicle is predicted to be higher than the probability that the host vehicle travels at the intersection before the first oncoming vehicle.

2. The other vehicle behavior prediction method as claimed in claim 1, characterized in that: When there is no second oncoming vehicle approaching the intersection on the road before the travel path of the host vehicle turns right or left at the intersection, a probability that the first oncoming vehicle travels at the intersection before the host vehicle is added.

3. The other vehicle behavior prediction method as claimed in claim 1, characterized in that: When there is a second oncoming vehicle approaching the intersection on the road before the vehicle's driving path turns right or left at the intersection, and the second oncoming vehicle stops in front of the intersection, the probability that the first oncoming vehicle reaches the intersection before the vehicle is added.

4. The other vehicle behavior prediction method as claimed in claim 1, characterized in that: When the speed of the first oncoming vehicle is equal to or higher than a predetermined speed value, a probability that the first oncoming vehicle travels at the intersection before the host vehicle is added.

5. The other vehicle behavior prediction method as claimed in claim 1, characterized in that: Based on the distance between the first oncoming vehicle and the center of the intersection, the distance between the first oncoming vehicle and the intersection is calculated.

6. The other vehicle behavior prediction method as claimed in claim 1, characterized in that: detecting the position of the stop line before the intersection, Based on the distance between the first oncoming vehicle and the stop line, the distance between the first oncoming vehicle and the intersection is calculated.

7. The other vehicle behavior prediction method as claimed in claim 1, characterized in that: When the priority of the road before the vehicle's driving path turns right or left at the intersection is higher than the priority of the road ahead after the vehicle's driving path turns right or left, the probability of the first oncoming vehicle entering the intersection before the vehicle is predicted based on the interval and the distance.

8. A driving assistance method, using the other vehicle behavior prediction method according to any one of claims 1 to 7, characterized in that: The travel of the host vehicle is controlled based on a result of predicting the probability that the first oncoming vehicle will travel at the intersection before the host vehicle.

9. The driving assistance method according to claim 8, characterized in that: When the probability that the first oncoming vehicle travels ahead of the host vehicle at the intersection is equal to or greater than a first predetermined value and less than a second predetermined value, the host vehicle starts to decelerate.

10. The driving assistance method according to claim 9, characterized in that: When the probability that the first oncoming vehicle travels ahead of the host vehicle at the intersection is greater than or equal to a second predetermined value and less than a third predetermined value, the host vehicle is slowed down.

11. The driving assistance method according to claim 10, characterized in that: When the probability that the first oncoming vehicle travels ahead of the host vehicle at the intersection is equal to or greater than a third predetermined value, the host vehicle is stopped before the intersection.

12. Another vehicle behavior prediction device, characterized in that: Calculate the vehicle's driving path. detecting a position of an intersection that is on a travel path of the host vehicle and within a predetermined distance from the host vehicle, Before the intersection, the positions of other vehicles around the vehicle are detected. When there is a first oncoming vehicle on the road ahead after the driving path of the host vehicle turns right or left at the intersection, calculating a vehicle passing area through which the host vehicle passes when traveling at the intersection and other vehicle passing areas through which the first oncoming vehicle is predicted to pass when traveling at the intersection, The shortest distance between the own vehicle passing area and the other vehicle passing area is calculated as the distance between the own vehicle passing area and the other vehicle passing area, calculating the distance between the first oncoming vehicle and the intersection, When the interval is smaller than a predetermined value of the interval and the distance is smaller than a predetermined value of the distance, the probability that the first oncoming vehicle travels at the intersection before the host vehicle is predicted to be higher than the probability that the host vehicle travels at the intersection before the first oncoming vehicle.

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