Driving assistance device, vehicle, and driving assistance method

Abstract

A driving assistance device according to an embodiment of the present disclosure is provided with a control unit configured to predict the possibility of a lane change by a first vehicle traveling in a first lane from the first lane to a second lane adjacent to the first lane. The control unit is further configured to, if the control unit predicts that a lane change by the first vehicle is possible, acquire time information representing an arrival time for the first vehicle to travel from the current travel position on the first lane to a limit line on the adjacent second lane, the limit line defining the maximum permissible travel position on the second lane during the lane change, and predict the degree of possibility of the lane change by the first vehicle on the basis of the acquired time information.

Description

Driving assistance device, vehicle, and driving assistance method

[0001] The present disclosure relates to a driving assistance device, a vehicle, and a driving assistance method.

[0002] BACKGROUND ART Various technologies have been disclosed as driving assistance devices and driving assistance methods for providing driving assistance to a target vehicle (see, for example, Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2021-060906

[0004] A driving assistance device according to an embodiment of the present disclosure includes a control unit configured to predict a possibility of a first vehicle traveling in a first lane changing from the first lane to a second lane adjacent to the first lane. When it is predicted that the first vehicle will change lanes, the control unit is configured to acquire time information representing an arrival time of the first vehicle from a current traveling position on the first lane of the first vehicle to a limit line that is a limit traveling position on the second lane that is a limit for the lane change, and further predict a degree of possibility of the first vehicle changing lanes based on the acquired time information.

[0005] A vehicle according to an embodiment of the present disclosure is equipped with the driving assistance device according to the embodiment of the present disclosure.

[0006] A driving assistance method according to an embodiment of the present disclosure includes predicting a possibility of a first vehicle traveling in a first lane changing from the first lane to a second lane adjacent to the first lane. Predicting the possibility of a lane change includes, when it is predicted that the first vehicle will change lanes, acquiring time information that is a time required for the first vehicle to reach a limit line that is a limit traveling position on the second lane that is a limit for the lane change from a current traveling position on the first lane of the first vehicle, and further predicting a degree of the possibility of the first vehicle changing lanes based on the acquired time information.

[0007] The accompanying drawings are included to provide a further understanding of the disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate one embodiment and, together with the description, serve to explain the principles of the disclosure.

[0008] FIG. 1 is a schematic diagram illustrating an example of a general configuration of a vehicle equipped with a driving assistance device according to a first embodiment of the present disclosure. FIG. 2 is a block diagram illustrating an example of a detailed configuration of the vehicle illustrated in FIG. 1. FIG. 3A is a flowchart illustrating an example of a driving assistance process according to the first embodiment. FIG. 3B is a flowchart illustrating an example of a driving assistance process subsequent to FIG. 3A. FIG. 4 is a schematic diagram for explaining the processing examples illustrated in FIGS. 3A and 3B. FIG. 5 is a flowchart illustrating an example of a driving assistance process according to Modification 1-1. FIG. 6 is a flowchart illustrating an example of a driving assistance process according to Modification 1-2. FIG. 7 is a flowchart illustrating a detailed processing example of a portion of the processing illustrated in FIG. 6. FIG. 8 is a schematic diagram for explaining the processing examples illustrated in FIGS. 6 and 7. FIG. 9 is a schematic diagram for explaining the processing example illustrated in FIG. 7. FIG. 10 is another schematic diagram for explaining the processing example illustrated in FIG. 7. FIG. 11 is a block diagram illustrating an example of a configuration of a vehicle equipped with a driving assistance device according to a second embodiment of the present disclosure. FIG. 12 is a flowchart illustrating an example of a driving assistance process according to the second embodiment. FIG. 13 is a flowchart illustrating an example of a driving assistance process according to the second modification.

[0009] In a driving assistance device or the like that provides driving assistance for a target vehicle, for example, it is required to improve the accuracy of prediction regarding the possibility of a vehicle (a vehicle other than the target vehicle) changing lanes. It is desirable to provide a driving assistance device, a vehicle, and a driving assistance method that can improve the accuracy of prediction regarding the possibility of a vehicle changing lanes.

[0010] Some exemplary embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Note that the following description illustrates one specific example of the present disclosure and should not be construed as limiting the present disclosure. For example, each element, including numerical values, shapes, materials, parts, the position of each part, and the connection method of each part, is merely an example and should not be construed as limiting the present disclosure. Furthermore, in the following exemplary embodiments, components not described in independent claims based on the highest concept of the present disclosure are optional and may be provided as needed. The drawings are schematic and are not intended to be drawn to scale. Throughout this specification and the drawings, components having substantially the same function and configuration are designated by the same reference numerals, and redundant description will be omitted. Furthermore, components not directly related to one embodiment of the present disclosure are not shown in the drawings.

[0011] 1. First embodiment> [Configuration] Fig. 1 is a schematic diagram illustrating an example of the overall configuration of a vehicle 3 equipped with a driving assistance device (a driving assistance device 111 described later) according to a first embodiment of the present disclosure. Fig. 2 is a block diagram illustrating an example of the detailed configuration of the vehicle 3 illustrated in Fig. 1.

[0012] 1 and 2, the vehicle 3 includes a vehicle control unit 11, a battery 12, a communication device 13, and a camera 14. As shown in FIG. 1, the vehicle 3 has an occupant 9 (such as a driver) on board.

[0013] (A. Vehicle Control Unit 11) The vehicle control unit 11 is a component (control unit) that controls various operations in the vehicle 3 and performs various arithmetic processing. Specifically, the vehicle control unit 11 includes, for example, one or more processors (CPU: Central Processing Unit) that execute programs, and one or more memories that are communicatively connected to these processors. Furthermore, such memories include, for example, RAM (Random Access Memory) that temporarily stores processing data, and ROM (Read Only Memory) that stores programs.

[0014] In the example shown in FIG. 2, the vehicle control unit 11 includes a driving assistance device 111, a battery control unit 112, a communication control unit 113, and a camera control unit 114.

[0015] (A-1. Driving assistance device 111) The driving assistance device 111 is a device that provides driving assistance for the target vehicle (vehicle 3), and in the example shown in Figure 2, it has an information acquisition unit 21, a prediction unit 22, a notification control unit 23, a notification unit 25, and a driving assistance unit 26.

[0016] The information acquisition unit 21 is a unit that acquires various types of information related to the vehicle 3. Specifically, in this embodiment, the information acquisition unit 21 acquires various types of information related to the vehicle 3 using the camera 14, various sensors, and the like as one of such various types of information.

[0017] More specifically, for example, the information acquisition unit 21 acquires various pieces of information related to the vehicle 3 in the following manner: - Measurement data related to the surrounding road structure and traffic participants is acquired using a stereo camera, LiDAR (Light Detection and Ranging), side radar, etc., and various image recognition processes and object determination processes are performed based on this measurement data, thereby making it possible to recognize the surrounding road structure and traffic participants; - The position of the vehicle (vehicle 3), the driving lane, the presence or absence of intersections, etc. is recognized using a GPS (Global Positioning System), high-precision map information, image matching processes, etc.; - Surrounding traffic environment information acquired from sensors such as surveillance cameras installed on the road and external camera systems of other vehicles different from the vehicle 3 is used for vehicle-to-vehicle communication and road-to-vehicle communication, making it possible to recognize information that cannot be obtained from the vehicle's sensors or map information, such as the number and other types of other vehicles that are blocked by other vehicles on the vehicle's route; - The state of the vehicle (vehicle 3) is acquired using a vehicle CAN (Controller Area Network), IMU (Inertial Measurement Unit), etc.

[0018] The prediction unit 22 is a unit that performs various prediction processes regarding the possibility of a lane change C12 (described later) being made by another vehicle (vehicle 1 described later) other than the vehicle 3. Details of such various prediction processes will be described later.

[0019] The notification control unit 23 is a unit that controls a predetermined notification operation in the notification unit 25 .

[0020] The notification unit 25 is a unit that performs a predetermined notification operation (notification processing) for the occupant 9 (such as the driver) of the vehicle 3. The notification unit 25 is configured to include, for example, a display unit (such as a display of various types) that performs a predetermined display operation as such a notification operation, and a tone output unit (such as a speaker of various types) that performs a predetermined audio output operation as such a notification operation.

[0021] The driving assistance unit 26 is a unit that provides driving assistance such as control of the driving operation of the vehicle 3 (driving control processing), and performs overall control related to the driving and the like of the vehicle 3. Specifically, the driving assistance unit 26 controls, for example, the drive system, braking system, steering system, and the like of the vehicle 3.

[0022] (A-2. Battery control unit 112, communication control unit 113, camera control unit 114) The battery control unit 112 is a unit that controls the operation (charging operation, discharging operation, etc.) of the battery 12. The communication control unit 113 is a unit that controls the communication operation of the communicator 13. The camera control unit 114 is a unit that controls the imaging operation of the camera 14.

[0023] (B. Battery 12, Communicator 13, Camera 14) The battery 12 is a component that functions as a power source for the vehicle 3, and is configured using various types of secondary batteries such as lithium ion batteries. The communicator 13 is a device that performs various types of communication with the outside of the vehicle 3 (for example, an information processing device such as a server provided outside the vehicle 3, or other vehicles other than the vehicle 3).

[0024] The camera 14 is a component that acquires imaging data relating to the outside (such as the surrounding environment of the vehicle 3) and the inside (such as the occupants 9 of the vehicle 3) of the vehicle 3. The imaging data acquired in this manner is supplied to, for example, the driving assistance device 111 (such as the information acquisition unit 21 described above) in the vehicle control unit 11.

[0025] [Operation, Function, and Effect] Next, the operation, function, and effect of this embodiment will be described in detail.

[0026] 3A and 3B are flowcharts illustrating an example of the driving assistance process according to the present embodiment (a processing example in the driving assistance device 111). Also, Fig. 4 is a schematic diagram for explaining the processing example shown in Figs. 3A and 3B.

[0027] In the example shown in FIG. 4 , vehicle 1 (a vehicle that is the subject of various predictions, described below) is traveling forward (in a traveling direction d1) on traveling lane L1, one of multiple traveling lanes (traffic lanes). Ahead of vehicle 1 on traveling lane L1, vehicle 2 is traveling (in a traveling direction d1). Furthermore, on traveling lane L2 adjacent (to the right of) traveling lane L1, vehicle 3 (host vehicle) is traveling forward (in a traveling direction d3), and multiple vehicles 4 are parked ahead of vehicle 3 on traveling lane L2 (in front of intersection Pc, described below). In the example of FIG. 4 , traveling lane L3 is also installed adjacent to the right of traveling lane L2.

[0028] 4, an intersection Pc is located ahead of the vehicles 2 and 4 on the driving lanes L1 and L2, and route directions dt1 to dt3 are defined for the driving lanes L1 to L3, respectively, just before the intersection Pc. Specifically, a route direction dt1 indicating a left turn is defined for the driving lane L1, a route direction dt2 indicating a straight ahead direction is defined for the driving lane L2, and a route direction dt3 indicating a right turn is defined for the driving lane L3.

[0029] Here, vehicle 1 corresponds to a specific example of a "first vehicle" in an embodiment of the present disclosure.

[0030] Furthermore, the driving lane L1 corresponds to a specific example of a "first lane" in one embodiment of the present disclosure, and the driving lane L2 corresponds to a specific example of a "second lane" in one embodiment of the present disclosure.

[0031] 3A and 3B, the prediction unit 22 first determines whether or not a vehicle 2 traveling in the driving lane L1 is present ahead of the vehicle 1 traveling in the driving lane L1 (step S11). If it is determined that no such vehicle 2 is present (step S11: N), the process returns to step S11.

[0032] On the other hand, as in the example of Figure 4, if it is determined that such a vehicle 2 exists (step S11: Y), the prediction unit 22 then makes the following determination. That is, the prediction unit 22 determines whether a vehicle 3 is traveling behind the vehicle 1 in the traveling lane L2 adjacent to the traveling lane L1 (step S12). Here, if it is determined that such a vehicle 3 does not exist (step S12: N), the process returns to step S11.

[0033] 4, when it is determined that such a vehicle 3 exists (step S12: Y), the prediction unit 22 then acquires the following information from the information acquisition unit 21. That is, the prediction unit 22 acquires information including, for example, the relative distance L12 and relative speed V12 between vehicle 1 and vehicle 2, the relative distance L34 between vehicle 3 and the above-mentioned vehicle 4, and an unusable situation period Δt13, which will be described below, as shown in FIG.

[0034] The impossibility period Δt13 is a period of time during which it is estimated that vehicle 1 is unable to change lanes C12 (from driving lane L1 to driving lane L2; see FIG. 4 ) due to the presence of vehicle 3 (see dashed arrow P13 in FIG. 4 ). Furthermore, the prediction unit 22 estimates that vehicle 1 is unable to change lanes C12 due to the presence of vehicle 3 when the relative distance L34 is equal to or less than a predetermined fifth threshold value Th5 (L34≧Th5).

[0035] Next, the prediction unit 22 determines whether or not a first condition C1 and a second condition C2, which will be described below, are satisfied based on the information acquired in step S13. Then, based on the determination results of the first condition C1 and the second condition C2, the prediction unit 22 predicts the possibility that the vehicle 1 will perform the lane change C12 described above.

[0036] Specifically, the prediction unit 22 first determines whether the following first condition C1 is satisfied (step S14). The first condition C1 is a condition that the relative distance L12 is equal to or greater than a predetermined first threshold value Th1 (L12≧Th1), and the first period Δt1 during which the absolute value |V12| of the relative velocity V12 is equal to or less than a predetermined second threshold value Th2 (|V12|≦Th2) continues for a period equal to or greater than a predetermined third threshold value Th3. Note that the first threshold value Th1 may be, for example, a table that defines the usual inter-vehicle distance of the vehicle 1 according to the traveling speed, or a typical inter-vehicle distance (e.g., 2 seconds).

[0037] The first condition C1 is determined for the following reason. For example, as shown in FIG. 4 , if vehicle 1 continues to not shorten the inter-vehicle distance (relative distance L12) with vehicle 2 despite there being sufficient space ahead of vehicle 1 (between vehicle 2) on driving lane L1, the following can be inferred. That is, this is considered to be an indication that vehicle 1 does not want to travel on the current driving lane L1. Therefore, if this condition continues for a period of time (first period Δt1) equal to or longer than a predetermined third threshold value Th3, it can be predicted that there is a high possibility that vehicle 1 will change lanes C12 from the current driving lane L1 to the adjacent driving lane L2.

[0038] If it is determined that the first condition C1 is not satisfied (step S14: N), the prediction unit 22 predicts that the vehicle 1 is unlikely to perform a lane change C12 (step S16). On the other hand, if it is determined that the first condition C1 is satisfied (step S14: Y), the prediction unit 22 then determines whether or not the second condition C2, which uses the unacceptable situation period Δt13 described above, is satisfied (step S15). The second condition C2 is a condition that the unacceptable situation period Δt13 continues for a period equal to or longer than a predetermined fourth threshold value Th4.

[0039] Here, if it is determined that the second condition C2 is not satisfied (step S15: N), the prediction unit 22 predicts that there is no possibility that the vehicle 1 will change lanes C12 (step S16). On the other hand, if it is determined that the second condition C2 is satisfied (step S15: Y), the prediction unit 22 predicts that there is a possibility that the vehicle 1 will change lanes C12 (step S17). In other words, if the determination result that both the first condition C1 and the second condition C2 are satisfied is obtained, the prediction unit 22 predicts that there is a possibility that the vehicle 1 will change lanes C12.

[0040] In this way, when the first condition C1 is satisfied (step S14: Y) even though it is estimated that the lane change C12 is not impossible due to the presence of vehicle 3 (step S15: N), the following intention of vehicle 1 is considered. That is, it can be said that vehicle 1 is highly likely to have an intention other than the lane change C12 (for example, the intention to slowly close the distance between vehicle 1 and vehicle 2 in order to avoid stopping at a stop light before intersection Pc if possible). Therefore, in this case, it can be predicted that there is no (low) possibility that vehicle 1 will change lanes C12.

[0041] At least one of the first threshold value Th1 and the second threshold value Th2 may be automatically adjustable (changeable) by the prediction unit 22, for example, depending on the presence and content of a sign or indicator restricting lane changes ahead of the vehicle 1. Examples of such signs or indicators restricting lane changes include signs or indicators defining the travel directions dt1 to dt3 shown in FIG. 4 , or lane markings (lane dividing lines) defined between adjacent travel lanes, restricting lane changes. In the example of FIG. 4 , this is because, if the prescribed travel directions of the travel lane L1 in which the vehicle 1 is traveling and the travel lane L2 adjacent to the travel lane L1 are different from each other, the vehicle 1 is more motivated to make a lane change C12. Therefore, specifically, when there is no sign or indicator restricting lane changes (or, even if there is a sign or indicator, the prescribed travel directions are the same), the threshold value is adjusted, for example, as follows, compared to when there is a sign or indicator restricting lane changes (or, when there is a sign or indicator, the prescribed travel directions are different from each other). In other words, in such a case, for example, the first threshold value Th1 may be adjusted to be relatively small, or the second threshold value Th2 may be adjusted to be relatively large, thereby making it easier to predict the possibility of vehicle 1 changing lanes C12 (relaxing the conditions for the first threshold value Th1 and the second threshold value Th2).

[0042] Subsequently, after each of the processes of steps S16 and S17 described above, the driving assistance unit 26 performs the following process. That is, in this case, the driving assistance unit 26 performs driving assistance (the above-mentioned driving control process, etc.) for the vehicle 3 in consideration of the prediction result regarding the lane change C12 of the vehicle 1 (the prediction result of steps S14 to S17 by the prediction unit 22) (step S18).

[0043] This completes the series of processing examples shown in FIGS. 3A and 3B.

[0044] (B. Actions and Effects) In this manner, in the present embodiment, the likelihood of vehicle 1 changing lanes C12 from traveling lane L1 to traveling lane L2 is predicted based on the results of determining whether or not the first condition C1 and the second condition C2 described above are respectively satisfied. As a result, the likelihood of vehicle 1 changing lanes C12 is predicted taking into account the situation ahead of vehicle 1 and a situation in which lane change C12 is impossible due to the presence of vehicle 3. As a result, in the present embodiment, it is possible to improve the accuracy of prediction of the likelihood of vehicle 1 changing lanes C12 compared to a case in which these situations are not taken into account.

[0045] Furthermore, in this embodiment, the driving assistance for the target vehicle (vehicle 3) is controlled taking into consideration the prediction result regarding the lane change C12 in vehicle 1, resulting in the following: That is, by early predicting the risk to surrounding vehicles due to such a lane change C12, it becomes possible to apply this to driving assistance such as early risk avoidance in vehicle 3.

[0046] 2. Modifications of the First Embodiment Next, modifications of the first embodiment (modifications 1-1 and 1-2) will be described. Note that, in the following, the same components as those in the first embodiment will be assigned the same reference numerals, and descriptions thereof will be omitted as appropriate.

[0047] [Modification 1-1] (Configuration and Operation) Figure 5 is a flowchart showing an example of driving assistance processing according to Modification 1-1. This example of driving assistance processing according to Modification 1-1 is the same as the example of driving assistance processing according to the first embodiment shown in Figures 3A and 3B, except that steps S21 and S22, which will be described below, are added between steps S17 and S18 (between step S17 and the destination of step S16). For convenience, steps S11 to S15 are not shown in Figure 5.

[0048] In step S21, if it is predicted in step S17 that the vehicle 1 may change lanes C12, the prediction unit 22 acquires, from the information acquisition unit 21, time information It, which is the arrival time Ta of the vehicle 1, as defined below. Specifically, as shown in FIG. 4 , for example, the prediction unit 22 acquires the arrival time Ta (time information It) of the vehicle 1 from the current driving position P1 in the driving lane L1 of the vehicle 1 to the limit driving position (limit line Lb) in the driving lane L2, which is the limit for the lane change C12. Note that this arrival time Ta is the distance (arrival distance La) from the current driving position P1 to the limit line Lb by the vehicle speed V1 of the vehicle 1 (Ta = La / V1).

[0049] In particular, in this modification 1-1, the first limit line Lb1 serving as the limit line Lb is determined as follows (see FIG. 4). That is, the first limit line Lb1 is determined based on the rear end position of a restricted area Ar (see FIGS. 9 and 10, described below) located ahead of the vehicle 1 on the driving lane L2, where lane changing or stopping is restricted. Alternatively, the first limit line Lb1 is determined based on the rear end position of a vehicle 4 (stopped vehicle) stopped ahead of the vehicle 1 on the driving lane L2. Note that in the example of FIG. 4, the first limit line Lb1 is determined based on the rear end position of the vehicle 4 stopped ahead of the vehicle 1 on the driving lane L2.

[0050] Subsequently, in step S22, the prediction unit 22 further predicts the degree of possibility of the vehicle 1 changing lanes C12 based on the time information It (=first time information It1: the arrival time Ta from the current traveling position P1 to the first limit line Lb1) acquired in step S21. In other words, in this modification 1-1, when it is predicted that the vehicle 1 is likely to change lanes C12, the prediction unit 22 further predicts the degree of possibility of the vehicle 1 changing lanes C12.

[0051] In step S22, the arrival time Ta of the vehicle 1 and the possibility of a lane change C12 have, for example, the following relationship:

[0052] That is, the prediction unit 22 predicts that the likelihood of the vehicle 1 changing lanes C12 increases as the arrival time Ta of the vehicle 1 decreases. Furthermore, the prediction unit 22A predicts that the likelihood of the vehicle 1 changing lanes C12 decreases when the arrival time Ta of the vehicle 1 is equal to or less than a predetermined threshold value Tath. Note that when the arrival time Ta is extremely short like this, it is difficult to actually change lanes C12, and therefore the likelihood of the vehicle 1 abandoning the lane change C12 increases, and conversely, the likelihood of the lane change C12 is predicted to decrease.

[0053] (Operations and Effects) In this modified example 1-1, the same effects as those in the first embodiment can be obtained by basically operating in the same manner.

[0054] Furthermore, particularly in this modified example 1-1, when it is predicted that there is a possibility of the vehicle 1 changing lanes C12, the arrival time Ta (time information It) of the vehicle 1 described above is acquired, and the degree of possibility of the vehicle 1 changing lanes C12 is further predicted based on this acquired time information It. In this way, in modified example 1-1, in addition to predicting whether or not there is a possibility of the vehicle 1 changing lanes C12, the degree of possibility of the vehicle 1 changing lanes C12 is also predicted, so it is possible to further improve the prediction accuracy of the possibility of the vehicle 1 changing lanes C12.

[0055] [Modification 1-2] (Configuration and Operation) Fig. 6 is a flowchart showing an example of the driving assistance process according to Modification 1-2, and Fig. 7 is a flowchart showing a detailed example of a part of the process (step S24 described later) shown in Fig. 6. Fig. 8 is a schematic diagram for explaining the process example shown in Fig. 6 and Fig. 7, and Fig. 9 and Fig. 10 are each a schematic diagram for explaining the process example shown in Fig. 7.

[0056] The driving assistance processing example according to Modification 1-2 is the same as the driving assistance processing example according to Modification 1-1 shown in Fig. 5, except that steps S23 and S24, which will be described below, are provided instead of steps S21 and S22. For convenience, steps S11 to S15 are not shown in Fig. 6.

[0057] In step S23 described above, if it is predicted in step S17 that there is a possibility that the vehicle 1 will change lanes C12, the prediction unit 22 acquires time information It, which is the arrival time Ta of the vehicle 1 defined as follows, from the information acquisition unit 21. Specifically, the prediction unit 22 acquires, as this time information It, the first time information It1 (the arrival time Ta from the current traveling position P1 to the first limit line Lb1) or the second time information It2 (the arrival time Ta from the current traveling position P1 to the second limit line Lb2) (see FIGS. 8 to 10).

[0058] Subsequently, in step S24, the prediction unit 22 further predicts the degree of possibility of the vehicle 1 changing lanes C12 based on the time information It (=first time information It1 or second time information It2) acquired in step S23. In detail, in step S24, the prediction unit 22 further predicts the degree of possibility of the vehicle 1 changing lanes C12 by using, for example, each process (steps S241 to S246) shown in FIG.

[0059] In the series of processes shown in FIG. 7 , the prediction unit 22 first predicts whether vehicle 1 will make a lane change C12 to a position behind vehicle 3 (step S241). Here, for example, as shown in FIG. 4 , if it is predicted that vehicle 1 will not make a lane change C12 to a position behind vehicle 3 (i.e., will make a lane change C12 to a position ahead of vehicle 3) (step S241: N), the following occurs. That is, in this case, the prediction unit 22 predicts the likelihood of vehicle 1 making a lane change C12 based on the first time information It1 (the arrival time Ta from the current traveling position P1 to the first limit line Lb1) acquired in step S23 (step S242: see FIG. 4 ). In this case, the process then proceeds to step S18 in FIG. 6 .

[0060] On the other hand, when it is predicted that vehicle 1 will make a lane change C12 to a position behind vehicle 3 (step S241: Y), as shown in Figures 8 to 10, the following occurs: In this case, the prediction unit 22 determines whether the rear end position P3 of vehicle 3 is located within the aforementioned restricted area Ar (see Figures 9 and 10) (step S243).

[0061] 9, if it is determined that the rear end position P3 of the vehicle 3 is not located within the restricted area Ar (step S243: N), the prediction unit 22 determines the second limit line Lb2 using the rear end position P3 of the vehicle 3 as a reference (step S244: see FIG. 9).

[0062] On the other hand, if it is determined that the rear end position P3 of the vehicle 3 is located within the restricted area Ar (step S243: Y), as shown in Figure 10, the prediction unit 22 determines the second limit line Lb2 using the rear end position Pr of the restricted area Ar as a reference (step S245: see Figure 10).

[0063] After steps S244 and S245, the prediction unit 22 predicts the likelihood of a lane change C12 of the vehicle 1 based on the second time information It2 (the arrival time Ta from the current traveling position P1 to the second limit line Lb2) acquired in step S23 (step S246: see FIGS. 9 and 10). In this case, the process then proceeds to step S18 in FIG. 6.

[0064] (Operations and Effects) In this modified example 1-2, the same effects as those in the first embodiment can be obtained by basically operating in the same manner.

[0065] Furthermore, particularly in this modification 1-2, when it is predicted that vehicle 1 will make a lane change C12 to a position behind vehicle 3, the aforementioned second time information It2 is acquired, and the degree of possibility of vehicle 1 making the lane change C12 is predicted based on the second time information It2 instead of the first time information It1. Furthermore, when it is predicted that the rear end position P3 of vehicle 3 will be located within the aforementioned restricted area Ar, the aforementioned second limit line Lb2 is determined based on the rear end position Pr of the restricted area Ar. On the other hand, when it is predicted that the rear end position P3 of vehicle 3 will not be located within the restricted area Ar, the second limit line Lb2 is determined based on the rear end position P3 of vehicle 3. In this way, in modification 1-2, when it is predicted that vehicle 1 will make a lane change C12 to a position behind vehicle 3, the degree of possibility of vehicle 1 making the lane change C12 is predicted taking into account whether or not the rear end position P3 of vehicle 3 will be located within the restricted area Ar. As a result, in this modified example 1-2, it is possible to further improve the prediction accuracy regarding the possibility of lane change C12 compared to modified example 1-1.

[0066] 3. Second Embodiment Next, a second embodiment of the present disclosure will be described. Note that, in the following, the same components as those in the first embodiment or modifications 1-1 and 1-2 will be denoted by the same reference numerals, and descriptions thereof will be omitted as appropriate.

[0067] 11 is a block diagram showing an example of the configuration of a vehicle (vehicle 3A) equipped with a driving assistance device (driving assistance device 111A) according to the second embodiment. The vehicle 3A of the second embodiment corresponds to the vehicle 3 (see FIG. 2) of the first embodiment, except that a vehicle control unit 11A including the driving assistance device 111A described below is provided instead of the vehicle control unit 11 including the driving assistance device 111 described above, and the other configurations are similar.

[0068] This driving assistance device 111A corresponds to the driving assistance device 111 in which a prediction unit 22A, which will be described below, is provided instead of the prediction unit 22 described above, and the other configurations are similar. That is, the driving assistance device 111A is a device that provides driving assistance for a target vehicle (vehicle 3A), and in the example shown in Fig. 11 includes an information acquisition unit 21, a prediction unit 22A, a notification control unit 23, a notification unit 25, and a driving assistance unit 26. The prediction unit 22A and the driving assistance unit 26 correspond to a specific example of a "control unit" in an embodiment of the present disclosure.

[0069] Similar to the prediction unit 22 described above, the prediction unit 22A is a unit that performs various prediction processes regarding the possibility of a lane change C12 (lane change) by another vehicle (vehicle 1) other than vehicle 3A. Furthermore, when the prediction unit 22A predicts that there is a possibility of a lane change C12 by vehicle 1, it further predicts the degree of possibility of the lane change C12 by vehicle 1 using the same method as in Modification 1-1 (using the processes of steps S21 and S22 shown in FIG. 5 ). That is, when it predicts that there is a possibility of a lane change C12, the prediction unit 22A acquires the arrival time Ta (time information It) of vehicle 1 from its current driving position P1 on driving lane L1 to a limit driving position (limit line Lb) on driving lane L2, which is the limit for the lane change C12. Then, based on the acquired time information It, the prediction unit 22A further predicts the degree of possibility of the lane change C12 by vehicle 1.

[0070] However, unlike prediction unit 22, this prediction unit 22A predicts the possibility of vehicle 1 changing lanes C12 not only by the processes of steps S11 to S15 described above, but also by using a broader, more generalized process (the process of step S31 described below).

[0071] [Operation and Effects] (Operation) Figure 12 is a flowchart illustrating an example of driving assistance processing according to this embodiment (example of processing in driving assistance device 111A). The example of driving assistance processing according to this embodiment is obtained by adding step S31, which will be described below, instead of steps S11 to S15 in the example of driving assistance processing according to Modification 1-1 shown in Figure 5. Note that vehicle 3 in this embodiment (and Modification 2, which will be described later) corresponds to a specific example of a "second vehicle" in an embodiment of the present disclosure.

[0072] In step S31, the prediction unit 22A determines whether a predetermined condition (a generic predetermined condition, not limited to the first condition C1 and the second condition C2 described above) related to the lane change C12 of the vehicle 1 is satisfied. If it is determined that the predetermined condition is not satisfied (step S31: N), the prediction unit 22A predicts that the vehicle 1 is unlikely to change lanes C12 (step S16). On the other hand, if it is determined that the predetermined condition is satisfied (step S31: Y), the prediction unit 22A predicts that the vehicle 1 is likely to change lanes C12 (step S17).

[0073] The subsequent steps S18, S21, and S22 are the same as the processes described above in Modification 1-1, and therefore will not be described here.

[0074] Incidentally, in step S22 shown in FIG. 12, as in step S22 shown in FIG. 5 and step S24 shown in FIG. 6, the following relationship exists between the arrival time Ta of the vehicle 1 and the possibility of lane change C12.

[0075] That is, the prediction unit 22A predicts that the possibility of the vehicle 1 changing lanes C12 increases as the arrival time Ta of the vehicle 1 decreases. Furthermore, the prediction unit 22A predicts that the possibility of the vehicle 1 changing lanes C12 decreases when the arrival time Ta of the vehicle 1 is equal to or less than a predetermined threshold value Tath.

[0076] (Functions and Effects) In this way, in the present embodiment, the degree of possibility of the vehicle 1 changing lanes C12 is further predicted in a manner basically similar to that of Modification 1-1 described above, and therefore, the same functions and effects as those of Modification 1-1 can be obtained. That is, in addition to predicting whether or not the vehicle 1 is likely to change lanes C12, the degree of possibility of the lane change C12 is also predicted, so that it is possible to further improve the prediction accuracy of the possibility of the lane change C12.

[0077] Also in this embodiment, the driving assistance for the target vehicle (vehicle 3A) is controlled taking into consideration the prediction result regarding the lane change C12 in vehicle 1, as follows: That is, by early predicting the risk to surrounding vehicles due to such a lane change C12, it becomes possible to apply this to driving assistance such as early risk avoidance in vehicle 3A.

[0078] 4. Modification of the Second Embodiment Next, a modification of the second embodiment (Modification 2) will be described. Note that, in the following, the same components as those in the first and second embodiments or Modifications 1-1 and 1-2 are denoted by the same reference numerals, and descriptions thereof will be omitted as appropriate.

[0079] [Modification 2] (Configuration and Operation) Fig. 13 is a flowchart showing an example of driving assistance processing according to Modification 2. This example of driving assistance processing according to Modification 2 is similar to the example of driving assistance processing according to Modification 1-2 shown in Fig. 6, except that step S31 described in the second embodiment is provided instead of steps S11 to S15.

[0080] That is, in this second modification, as in the second embodiment, the prediction unit 22A determines whether a predetermined condition (a generic predetermined condition, not limited to the first condition C1 and the second condition C2 described above) related to the lane change C12 of the vehicle 1 is satisfied (step S31). If it is determined that the predetermined condition is not satisfied (step S31: N), the prediction unit 22A predicts that the vehicle 1 is unlikely to change lanes C12 (step S16). On the other hand, if it is determined that the predetermined condition is satisfied (step S31: Y), the prediction unit 22A predicts that the vehicle 1 is likely to change lanes C12 (step S17).

[0081] The subsequent steps S18, S23, and S24 are the same as the processes described above in Modification 1-2, and therefore will not be described here.

[0082] Incidentally, in step S22 shown in FIG. 13, as in step S22 shown in FIGS. 5 and 12 and step S24 shown in FIG. 6, the following relationship exists between the arrival time Ta of the vehicle 1 and the possibility of lane change C12, for example:

[0083] That is, the prediction unit 22A predicts that the possibility of the vehicle 1 changing lanes C12 increases as the arrival time Ta of the vehicle 1 decreases. Furthermore, the prediction unit 22A predicts that the possibility of the vehicle 1 changing lanes C12 decreases when the arrival time Ta of the vehicle 1 is equal to or less than a predetermined threshold value Tath.

[0084] (Operations and Effects) In the second modification, basically, the same operations as those in the second embodiment can be performed, and the same effects can be obtained.

[0085] Furthermore, in particular, in this Modification 2, similar to the above-described Modification 1-2, when it is predicted that vehicle 1 will make a lane change C12 to a position behind vehicle 3, the degree of possibility of vehicle 1 making the lane change C12 is predicted taking into consideration whether or not the rear end position P3 of vehicle 3 is located within the restricted area Ar. As a result, in this Modification 2, it is possible to further improve the prediction accuracy of the possibility of vehicle 1 making the lane change C12 compared to the second embodiment.

[0086] 5. Other Modifications The present disclosure has been described above by giving several embodiments and modifications, but the present disclosure is not limited to these embodiments and can be modified in various ways.

[0087] For example, the configuration (type, arrangement, number, etc.) of each component in a vehicle or the like is not limited to that described in the above embodiment, etc. In other words, the configuration of each component may be of a different type, arrangement, number, etc. Specifically, for example, in the above embodiment, etc., an example has been described in which the driving assistance device in one embodiment of the present disclosure is provided in a vehicle that is a target of driving assistance, but this example is not limiting. In other words, at least some of the components in the driving assistance device (such as the information acquisition unit, prediction unit, notification control unit, and driving assistance unit) may be provided, for example, inside a server (information processing device) or the like that is provided outside the target vehicle.

[0088] Furthermore, in the above embodiments, various processing examples (such as the various prediction processing and driving assistance processing described above) have been specifically described, but the present invention is not limited to the methods described in the above embodiments, and other methods may be used, for example.

[0089] Furthermore, the values, ranges, magnitude relationships, etc. of the various parameters described in the above embodiments are not limited to those described in the above embodiments, but may be other values, ranges, magnitude relationships, etc.

[0090] In addition, in the above embodiment and the like, an example has been described in which the host vehicle, vehicle 3, is the "second vehicle" in one embodiment of the present disclosure, but this is not limiting. That is, for example, a vehicle different from the host vehicle may be set as the "second vehicle" in one embodiment of the present disclosure.

[0091] Additionally, in the above-described embodiment and the like, an example has been described in which the battery 12 is provided as a power source in the vehicle 3. That is, in the above-described embodiment and the like, an example has been described in which the vehicle 3 is an electric vehicle (EV) or a hybrid electric vehicle (HEV), but this is not limiting. That is, for example, the vehicle 3 may be a gasoline vehicle or a fuel-powered vehicle, etc.

[0092] Furthermore, the series of processes described in the above embodiments may be performed by hardware (circuits), software (programs), or a combination of hardware and software. When performed by software, the software is composed of a group of programs for causing a computer to execute each function. Each program may be, for example, pre-installed in the computer, or may be installed on the computer from a network or recording medium.

[0093] Furthermore, the various examples described above may be applied in any combination.

[0094] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0095] The present disclosure may also be configured as follows: (1) A driving assistance device including a control unit configured to predict a possibility of a first vehicle traveling on a first lane changing from the first lane to a second lane adjacent to the first lane, wherein the control unit is configured, when it is predicted that the first vehicle will change lanes, to acquire time information that is an arrival time of the first vehicle from a current traveling position on the first lane of the first vehicle to a limit line that is a limit traveling position on the second lane that becomes a limit for the lane change, and to further predict a degree of the possibility of the first vehicle changing lanes based on the acquired time information. (2) The driving assistance device described in (1) above, wherein the first limit line as the limit line is determined based on the rear end position of a restricted area in front of the first vehicle on the second lane where lane changing or stopping is restricted, or the rear end position of a stopped vehicle stopped in front of the first vehicle on the second lane, and the first time information as the time information is the arrival time of the first vehicle from the current driving position to the first limit line. (3) The control unit is configured to, when a second vehicle is present traveling behind the first vehicle on the second lane and it is predicted that the first vehicle will change lanes to a position behind the second vehicle, acquire second time information that is the arrival time of the first vehicle from the current traveling position to a second limit line as the limit traveling position, and predict the degree of possibility of the lane change by the first vehicle based on the acquired second time information instead of the first time information; when it is predicted that the rear end position of the second vehicle will be located within the restricted area, the second limit line is determined based on the rear end position of the restricted area; and when it is predicted that the rear end position of the second vehicle will not be located within the restricted area, the second limit line is determined based on the rear end position of the second vehicle. The driving assistance device described in (2) above.(4) The driving assistance device according to any one of (1) to (3), wherein the control unit is configured to predict that the likelihood of the first vehicle changing lanes will increase as the arrival time of the first vehicle becomes shorter. (5) The driving assistance device according to (4), wherein the control unit is configured to predict that the likelihood of the first vehicle changing lanes will decrease if the arrival time of the first vehicle is equal to or less than a predetermined threshold. (6) The driving assistance device according to any one of (1) to (5), wherein the control unit controls driving assistance of a target vehicle by taking into account a prediction result regarding the lane change of the first vehicle. (7) A vehicle comprising the driving assistance device according to any one of (1) to (6). (8) The vehicle according to (7), wherein the vehicle is a second vehicle traveling behind the first vehicle on the second lane. (9) A driving assistance method including predicting the possibility of a first vehicle traveling in a first lane changing from the first lane to a second lane adjacent to the first lane, wherein predicting the possibility of the lane change includes: when it is predicted that the first vehicle will change lanes, acquiring time information that is the time it will take the first vehicle to reach a limit line that is a limit driving position on the second lane that is a limit for the lane change from the current driving position of the first vehicle on the first lane; and further predicting the degree of the possibility of the first vehicle changing lanes based on the acquired time information.

[0096] The vehicle control unit 11 shown in FIGS. 1 and 2 and the vehicle control unit 11A shown in FIG. 11 may be implemented by a circuit including at least one semiconductor integrated circuit, such as at least one processor (e.g., a central processing unit (CPU)), at least one application-specific integrated circuit (ASIC), and / or at least one field-programmable gate array (FPGA). The at least one processor may be configured to execute all or part of the various functions of the vehicle control unit 11 shown in FIGS. 1 and 2 and the vehicle control unit 11A shown in FIG. 11 by reading instructions from at least one non-transitory, tangible computer-readable medium. Such medium may take various forms, including, but not limited to, various magnetic media such as hard disks, various optical media such as CDs or DVDs, and various semiconductor memories (i.e., semiconductor circuits) such as volatile or non-volatile memories. Volatile memory may include DRAM and SRAM. Non-volatile memory may include ROM and NVRAM. An ASIC is an integrated circuit (IC) specialized to execute all or part of the various functions of the vehicle control unit 11 shown in Figures 1 and 2 and the vehicle control unit 11A shown in Figure 11. An FPGA is an integrated circuit designed to be configurable after manufacture to execute all or part of the various functions of the vehicle control unit 11 shown in Figures 1 and 2 and the vehicle control unit 11A shown in Figure 11.

Claims

1. A driving assistance device comprising: a control unit configured to predict the possibility of a first vehicle traveling in a first lane changing from the first lane to a second lane adjacent to the first lane, wherein the control unit is configured, when it is predicted that the first vehicle will change lanes, to acquire time information that is the time it will take the first vehicle to reach a limit line that is the limit driving position on the second lane that is the limit for the lane change, from the current driving position on the first lane of the first vehicle, and to further predict the degree of possibility of the first vehicle changing lanes based on the acquired time information.

2. The driving assistance device of claim 1, wherein the first limit line as the limit line is determined based on the rear end position of a restricted area in front of the first vehicle on the second lane where lane changing or stopping is restricted, or the rear end position of a stopped vehicle stopped in front of the first vehicle on the second lane, and the first time information as the time information is the arrival time of the first vehicle from the current driving position to the first limit line.

3. The control unit is configured to, when a second vehicle is present traveling behind the first vehicle on the second lane and it is predicted that the first vehicle will change lanes to a position behind the second vehicle, acquire second time information that is the arrival time of the first vehicle from the current traveling position to a second limit line as the limit traveling position, and predict the degree of possibility of the first vehicle changing lanes based on the acquired second time information instead of the first time information; when it is predicted that the rear end position of the second vehicle will be located within the restricted area, the second limit line is determined based on the rear end position of the restricted area; and when it is predicted that the rear end position of the second vehicle will not be located within the restricted area, the second limit line is determined based on the rear end position of the second vehicle. A driving assistance device as described in claim 2.

4. A driving assistance device as described in any one of claims 1 to 3, wherein the control unit is configured to predict that the likelihood of the first vehicle changing lanes increases as the arrival time of the first vehicle becomes shorter.

5. The driving assistance device according to claim 4, wherein the control unit is configured to predict that the possibility of the first vehicle changing lanes will decrease if the arrival time of the first vehicle is equal to or less than a predetermined threshold.

6. A driving assistance device according to any one of claims 1 to 3, wherein the control unit controls driving assistance in the target vehicle by taking into account the prediction result regarding the lane change in the first vehicle.

7. A vehicle equipped with a driving assistance device according to any one of claims 1 to 3.

8. The vehicle according to claim 7, wherein the vehicle is a second vehicle traveling behind the first vehicle on the second lane.

9. A driving assistance method including predicting the possibility of a first vehicle traveling in a first lane changing from the first lane to a second lane adjacent to the first lane, wherein predicting the possibility of the lane change includes: when it is predicted that the first vehicle will change lanes, acquiring time information that is the time it will take the first vehicle to reach a limit line that is a limit driving position on the second lane that is the limit for the lane change from the current driving position of the first vehicle on the first lane; and further predicting the degree of possibility of the first vehicle changing lanes based on the acquired time information.

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