Driving assistance device, vehicle, and driving assistance method

Abstract

A driving assistance device according to an embodiment of the present disclosure comprises a control unit configured such that in a situation where, in front of a first vehicle traveling in a first lane, a second vehicle is traveling in a second lane different from the first lane, one or more first route directions are defined on the first lane, and one or more second route directions different from the one or more first route directions are defined on each of the second lane and one or more third lanes positioned between the first lane and the second lane, the control unit predicts the possibility that the second vehicle will make a continuous lane change from the second lane toward the first lane across the third lane. The control unit is configured to predict the possibility that the second vehicle will make a continuous lane change on the basis of a prediction result indicating whether there is an intention for the second vehicle to advance in the one or more second route directions.

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 likelihood of the second vehicle making a consecutive lane change from the second lane across the third lane toward the first lane, in a situation where a second vehicle is traveling in a second lane different from the first lane ahead of a first vehicle traveling in a first lane, one or more first course directions are defined on the first lane, and one or more second course directions different from the first course direction are defined on one or more third lanes located between the first lane and the second lane and on the second lane, respectively. The control unit is configured to predict the likelihood of the second vehicle making a consecutive lane change based on a prediction result of whether or not the second vehicle intends to proceed in the second course direction.

[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 likelihood of the second vehicle making a continuous lane change from the second lane across the third lane to the first lane, in a situation where a second vehicle is traveling in a second lane different from the first lane ahead of a first vehicle traveling in a first lane, one or more first course directions are defined on the first lane, and one or more second course directions different from the first course direction are defined on one or more third lanes located between the first and second lanes and on the second lane, respectively. Predicting the likelihood of making a continuous lane change includes predicting a likelihood of the second vehicle making a continuous lane change based on a prediction result of whether or not the second vehicle intends to proceed in the second course direction.

[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 an 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 an 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 example illustrated in FIGS. 3A and 3B. FIG. 5 is another schematic diagram for explaining the processing example illustrated in FIGS. 3A and 3B. FIG. 6 is another schematic diagram for explaining the processing example illustrated in FIGS. 3A and 3B. FIG. 7A is a flowchart illustrating an example of a driving assistance process according to Modification 1. FIG. 7B is a flowchart illustrating an example of a driving assistance process subsequent to FIG. 7A. FIG. 8 is a schematic diagram for explaining an example of a driving assistance process according to Modification 2.

[0009] In a driving assistance device or the like that provides driving assistance for a target vehicle, for example, it is required to quickly predict the possibility of a vehicle (a vehicle other than the target vehicle) making successive lane changes (successive lane changes across a driving lane as a predetermined lane). It is desirable to provide a driving assistance device, a vehicle, and a driving assistance method that can quickly predict the possibility of a vehicle making successive lane changes.

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

[0012] 1 and 2, the vehicle 1 includes a vehicle control unit 11, a battery 12, a communication device 13, and a camera 14. As shown in FIG. 1, the vehicle 1 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 1 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 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 1), 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 1. Specifically, in this embodiment, the information acquisition unit 21 acquires various types of information related to the vehicle 1 using the camera 14, various sensors, etc. 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 1 in the following manner: - Measurement data related to the surrounding road structure and traffic participants can be acquired using a stereo camera, LiDAR (Light Detection and Ranging), side radar, etc., and various image recognition processes and object determination processes can be performed based on this measurement data to recognize the surrounding road structure and traffic participants; - The position of the vehicle (vehicle 1), the driving lane, the presence or absence of intersections, etc. can be 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 from external camera systems of other vehicles different from the vehicle 1 can be recognized using vehicle-to-vehicle communication and road-to-vehicle communication to recognize information that cannot be obtained from the vehicle's sensors or map information, such as the number and presence of other vehicles on the vehicle's route that are blocked by other vehicles; - The status of the vehicle (vehicle 1) can be 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 continuous lane change C12 (continuous lane change across a predetermined driving lane) to be performed by another vehicle (vehicle 2 to be described later) different from vehicle 1. 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 1. 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 1 (driving control processing), and performs overall control related to the driving, etc. of the vehicle 1. Specifically, the driving assistance unit 26 controls, for example, the drive system, braking system, steering system, etc. of the vehicle 1.

[0022] The prediction unit 22 and the driving support unit 26 described above correspond to a specific example of a "control unit" in an embodiment of the present disclosure.

[0023] (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.

[0024] (B. Battery 12, Communicator 13, Camera 14) The battery 12 is a component that functions as a power source for the vehicle 1, 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 1 (for example, an information processing device such as a server provided outside the vehicle 1, or other vehicles other than the vehicle 1).

[0025] The camera 14 is a component that acquires imaging data relating to the outside (such as the surrounding environment of the vehicle 1) and the inside (such as the occupants 9 of the vehicle 1) of the vehicle 1. 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.

[0026] [Operation, Function, and Effect] Next, the operation, function, and effect of this embodiment will be described in detail.

[0027] 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). FIGS. 4 to 6 are schematic diagrams for explaining the processing examples shown in FIGS. 3A and 3B, respectively.

[0028] 4 to 6, of the multiple driving lanes (traffic lane), vehicle 1 (host vehicle) is traveling forward (in driving direction P1) on driving lane L1, and vehicle 2 (various vehicles that are the subject of predictions, which will be described later) is traveling forward on driving lane L2. Furthermore, one or more driving lanes (in this example, one driving lane L3) are installed between these driving lanes L1 and L2, and in the examples of FIGS. 4 and 5, driving lane L4 is installed to the right of driving lane L1 (the opposite side from the installation direction of driving lane L3).

[0029] In each of the examples shown in Figures 4 to 6, an intersection Pc is located ahead of vehicles 1 and 2 on driving lanes L1 and L2. In particular, in the examples shown in Figures 5 and 6, multiple stopped vehicles 8 are parked ahead of vehicles 1 and 2 on driving lanes L1 and L2 (before the intersection Pc). In each of the examples shown in Figures 4 to 6, one or more course directions d1 (in this example, a right-turn direction) are defined on driving lane L1. Meanwhile, one or more course directions d2 (in this example, a left-turn direction or a straight-ahead direction) different from the course direction d1 are defined on driving lanes L2 and L3. Thus, in each of the examples shown in Figures 4 to 6, the course directions d1 and d2 are defined by the intersection Pc located ahead of vehicles 1 and 2. However, these course directions d1 and d2 may also be defined by a course branch point located ahead of vehicles 1 and 2.

[0030] Here, vehicle 1 corresponds to a specific example of a "first vehicle" in an embodiment of the present disclosure, and vehicle 2 corresponds to a specific example of a "second vehicle" in an embodiment of the present disclosure. Furthermore, driving lane L1 corresponds to a specific example of a "first lane" in an embodiment of the present disclosure, driving lane L2 corresponds to a specific example of a "second lane" in an embodiment of the present disclosure, and driving lane L3 corresponds to a specific example of a "third lane" in an embodiment of the present disclosure. Furthermore, course direction d1 corresponds to a specific example of a "first course direction" in an embodiment of the present disclosure, and course direction d2 corresponds to a specific example of a "second course direction" in an embodiment of the present disclosure. Furthermore, driving lanes L1 and L4 each correspond to a specific example of a "first course direction lane" in an embodiment of the present disclosure.

[0031] 3A and 3B, the prediction unit 22 first determines whether or not a vehicle 2 traveling in a different lane L2 is present ahead of the vehicle 1 traveling in the lane L1 (step S11 in FIG. 3A). If it is determined that no such vehicle 2 is present (step S11: N), the process returns to step S11.

[0032] 4 to 6, if it is determined that such a vehicle 2 exists (step S11: Y), the prediction unit 22 then performs the following determination. That is, the prediction unit 22 determines whether the course direction d1 on the driving lane L1 and the course direction d2 on the driving lane L2 and the driving lane L3 (located between the driving lanes L1 and L2) are different from each other (d1 ≠ d2) (step S12). Here, if it is determined that these course directions d1 and d2 are equal to each other (d1 = d2) (step S12: N), the process returns to step S11.

[0033] On the other hand, when it is determined that the course directions d1 and d2 are different from each other (d1 ≠ d2) (step S12: Y), as in the examples of FIGS. 4 to 6 , the prediction unit 22 then makes the following determination. That is, the prediction unit 22 predicts and detects whether or not the vehicle 2 will indicate an intention to change lanes P2 (see FIGS. 4 to 6 ) (step S13). Specifically, the prediction unit 22 predicts and detects whether or not the vehicle 2 will indicate an intention to change lanes P2 by using, for example, the illumination status of the turn signal of the vehicle 2 or a preparatory movement for a lane change, such as the vehicle 2 moving toward an adjacent lane (in the examples of FIGS. 4 to 6 , the driving lane L3).

[0034] If it is determined that the vehicle 2 has not detected a lane change intention P2 (step S13: N), the prediction unit 22 makes the following determination. That is, in this case, the prediction unit 22 predicts that there is a high possibility that the vehicle 2 intends to proceed in the travel direction d2, and as a result, there is a low possibility that the vehicle 2 will make successive lane changes C12 (step S14). These successive lane changes C12 by the vehicle 2 refer to, for example, successive lane changes from the driving lane L2 across the driving lane L3 toward the driving lane L1, as shown in FIGS. 4 to 6 . In this case, the process then proceeds to step S19, which will be described later.

[0035] On the other hand, if it is determined that the vehicle 2 has detected an indication of intention to change lanes P2 (step S13: Y), the prediction unit 22 makes the following prediction: In this case, the prediction unit 22 predicts that there is a high possibility that the vehicle 2 has no intention to proceed in the direction of travel d2, and as a result, there is a high possibility that the vehicle 2 will perform the above-mentioned successive lane changes C12 (step S15). In this case, the process then proceeds to step S16, which will be described later.

[0036] In this way, the prediction unit 22 predicts whether or not the vehicle 2 intends to proceed in the direction of travel d2, based on the detection result of the lane change intention expression P2 of the vehicle 2. Furthermore, the prediction unit 22 predicts the possibility that the vehicle 2 will perform successive lane changes C12, based on the prediction result of whether or not the vehicle 2 intends to proceed in the direction of travel d2.

[0037] Specifically, in the example shown in Figure 4, if vehicle 2 intends to proceed in direction d2 (turn left), it is considered that there is no benefit to vehicle 2 deliberately changing lanes to the driving lane L1 side, which is defined as direction d1 (turn right). In other words, when vehicle 2 indicates its intention to change lanes P2, it is predicted that vehicle 2 has no intention to proceed in direction d2, but rather has an intention to proceed in direction d1. From these facts, in the example of Figure 4, it can be predicted that there is a high possibility that vehicle 2 will perform the above-mentioned consecutive lane change C12.

[0038] Next, in step S16, the prediction unit 22 acquires congestion information It for each driving lane (in the examples of FIGS. 4 to 6, driving lanes L1 to L3 or L1 to L4) from the information acquisition unit 21 (step S16). Next, the prediction unit 22 determines whether the traffic congestion volume Vt2 in driving lane L2 is less than the traffic congestion volume Vt3 in driving lane L3 (Vt2<Vt3) (step S17 in FIG. 3B). Conversely, if the prediction unit 22 determines that the traffic congestion volume Vt2 in driving lane L2 is greater than or equal to the traffic congestion volume Vt3 in driving lane L3 (Vt2≧Vt3) (step S17: N), the process proceeds to step S19 (described below).

[0039] On the other hand, if it is determined that the traffic congestion volume Vt2 in the driving lane L2 is less than the traffic congestion volume Vt3 in the driving lane L3 (Vt2<Vt3) (step S17: Y), the prediction unit 22 makes the following prediction: In this case, the prediction unit 22 predicts that there is an even higher possibility that the vehicle 2 has no intention of proceeding in the direction of travel d2, and as a result, there is an even higher possibility that the vehicle 2 will perform the above-mentioned consecutive lane change C12 (step S18). In this case, the process then proceeds to step S19, which will be described later.

[0040] In this way, the prediction unit 22 also uses the congestion information It for each driving lane, including the driving lanes L2 and L3, to predict whether or not the vehicle 2 intends to proceed in the direction d2.

[0041] Specifically, in the example shown in FIG. 5 , multiple stopped vehicles 8 are parked ahead of vehicles 1 and 2 in driving lanes L2 and L3, and the traffic congestion volume Vt2 in driving lane L2 is less than the traffic congestion volume Vt3 in driving lane L3 (Vt2<Vt3). Therefore, if vehicle 2 intends to proceed in direction d2 (turning left), it is considered that there is even less merit in vehicle 2 making a lane change than in the example shown in FIG. 4 . In other words, if vehicle 2 intends to proceed in direction d2, it is more efficient to remain in lane L2, which has the least traffic congestion volume, of the driving lanes (in this example, two driving lanes L2 and L3) in which direction d2 is defined. Despite this situation, when vehicle 2 indicates its intention to change lanes P2, it is predicted that vehicle 2 is more likely to have no intention of proceeding in direction d2 and to have an intention of proceeding in direction d1 (turning right). From these facts, it can be predicted that in the example of FIG. 5, the possibility of the vehicle 2 making the above-mentioned successive lane changes C12 is even higher.

[0042] In the example shown in Figure 6, the lane L4 is not located to the right of the lane L1 in the example shown in Figure 5, and the direction of travel d2 on lane L2 includes both a left turn and a straight-ahead direction, while the direction of travel d2 on lane L3 includes a straight-ahead direction. In this example shown in Figure 6, when vehicle 2 indicates its intention to change lanes P2, it is predicted that vehicle 2 has no intention of proceeding in direction d2 (a left turn or a straight-ahead direction) and is more likely to have an intention of proceeding in direction d1 (a right turn). This is because, if vehicle 2 intends to proceed in a left turn or a straight-ahead direction, it is more efficient to remain in lane L2, which has the least congestion, of the lanes L2 and L3 that share the direction of travel d2. For these reasons, it can be predicted that vehicle 2 is even more likely to perform the continuous lane change C12 described above in the example shown in Figure 6.

[0043] Next, the driving assistance unit 26 performs driving assistance (such as the aforementioned driving control processing) in vehicle 1, taking into account the prediction results regarding continuous lane changes C12 in vehicle 2 (prediction results in steps S13 to S18 by the prediction unit 22) (step S19).

[0044] This completes the series of processing examples shown in FIGS. 3A and 3B.

[0045] (B. Actions and Effects) In this manner, in the present embodiment, the likelihood of the vehicle 2 making a consecutive lane change C12 (changing lanes from driving lane L2 to driving lane L1 across driving lane L3) is predicted based on the prediction result of whether or not the vehicle 2 intends to proceed in the travel direction d2. This enables a timely prediction of the likelihood of the vehicle 2 making a consecutive lane change C12 compared to, for example, using historical information about past lane changes by the vehicle 2. As a result, in the present embodiment, it is possible to quickly predict the likelihood of the vehicle 2 making a consecutive lane change C12.

[0046] Furthermore, in this embodiment, the presence or absence of an intention to proceed in the direction d2 of travel is predicted based on the detection result of the lane change intention indication P2 of the vehicle 2, so it is possible to easily predict the presence or absence of an intention to proceed in the direction d2 of the vehicle 2. As a result, it is possible to more quickly predict the possibility of the vehicle 2 making a successive lane change C12.

[0047] Furthermore, in this embodiment, the presence or absence of the vehicle 2's intention to proceed in the travel direction d2 is predicted using the congestion information It for each travel lane, including the travel lanes L2 and L3, so that the presence or absence of such intention can be predicted with high accuracy. As a result, it is possible to improve the accuracy of predicting the possibility of the vehicle 2 making successive lane changes C12.

[0048] Additionally, in this embodiment, the driving assistance for the target vehicle (vehicle 1) is controlled in consideration of the prediction result regarding the successive lane changes C12 in vehicle 2, resulting in the following: That is, by predicting the risk to surrounding vehicles due to such successive lane changes C12 early, it becomes possible to apply this to driving assistance such as early risk avoidance in vehicle 1.

[0049] 2. Modifications Next, modifications of the above embodiment (modifications 1 and 2) will be described. Note that, in the following, the same components as those in the embodiment will be given the same reference numerals, and descriptions thereof will be omitted as appropriate.

[0050] [Modification 1] (Configuration and Operation) Figures 7A and 7B are flowcharts illustrating an example of driving assistance processing according to Modification 1. This example of driving assistance processing according to Modification 1 is obtained by adding step S20, which will be described below, between steps S18 and S19 (between the destination in the case of (S17: N) and the destination in the case of (S14: N)) in the example of driving assistance processing according to the embodiment shown in Figures 3A and 3B. Note that for convenience, steps S11 and S12 are not shown in Figure 7A.

[0051] In step S20 (see FIG. 7B ), if the prediction unit 22 predicts that the vehicle 2 is likely to make the aforementioned consecutive lane changes C12, the prediction unit 22 further predicts the destination lane (lane) to which the vehicle 2 will change during the consecutive lane changes C12, as will be described in detail below. In this case, the prediction unit 22 predicts a driving lane that does not include the course direction d2 defined on the driving lanes L2 and L3 as its course direction (for example, the driving lane Ld1 defined with the aforementioned course direction d1) as the destination lane (lane) to which the vehicle 2 will change during the consecutive lane changes C12.

[0052] Furthermore, when there are multiple driving lanes Ld1 for which such a course direction d1 is defined (in the examples of FIGS. 4 and 5 , there are two driving lanes L1 and L4 as the driving lanes Ld1), the prediction unit 22 predicts the destination lane to be changed to during the consecutive lane change C12, for example, as follows: That is, the prediction unit 22 predicts, among the multiple driving lanes Ld1, the driving lane Ld1 with the least amount of congestion or the driving lane Ld1 closest to the driving lane L2 before the consecutive lane change C12 was performed (the driving lane L2 is currently being driven), as the destination lane to be changed to during the consecutive lane change C12.

[0053] Specifically, in the example shown in Figure 5, if it is predicted that vehicle 2 intends to proceed in direction d1 (right turn) (i.e., there is a possibility of making a consecutive lane change C12), the destination lane for the consecutive lane change C12 is predicted as follows. That is, in this case, first, two travel lanes L1 and L4, which are travel lane Ld1 for which direction d1 is specified, are predicted as candidate destination lanes for the consecutive lane change C12. In the example shown in Figure 5, the amount of traffic congestion in these two travel lanes L1 and L4 is approximately the same, so as described above, the travel lane L1, which is the travel lane Ld1 closest to travel lane L2, is predicted as the destination lane for the consecutive lane change C12.

[0054] The above-described driving lanes L1 and L4 (driving lane Ld1 in which the course direction d1 is defined) each correspond to a specific example of a "first course direction lane" in one embodiment of the present disclosure.

[0055] (Operations and Effects) In this first modification, the same effects as those in the above-described embodiment can be obtained by basically operating in the same manner.

[0056] Furthermore, in particular, in this modification 1, when it is predicted that the vehicle 2 is likely to make successive lane changes C12, the destination lane of the successive lane changes C12 is further predicted, resulting in the following: In other words, in addition to the possibility of making successive lane changes C12, the destination lane of the successive lane changes C12 is also predicted, making it possible to accurately predict the risk to surrounding vehicles due to the successive lane changes C12.

[0057] [Modification 2] (Configuration and Operation) Figure 8 is a schematic diagram for explaining an example of driving assistance processing according to Modification 2, which is obtained by adding a vehicle 3 traveling on driving lane L3 to the example of Figure 4 described above. This example of driving assistance processing according to Modification 2 is the same as the example of driving assistance processing according to the embodiment and Modification 1 described so far, but with the addition of prediction processing, which will be described below.

[0058] That is, in this example of the driving assistance process according to Modification 2, the prediction unit 22 further predicts the degree of possibility (level) of consecutive lane changes C12 by vehicle 2, taking into account the presence of other vehicles (vehicles 1 and 3 in the example of FIG. 8 ) traveling behind vehicle 2. Specifically, the prediction unit 22 further predicts the degree of possibility of consecutive lane changes C12, for example, based on predetermined parameters (at least one of relative speed V12 and relative distance L12) indicating the relative relationship between vehicle 2 and vehicle 1. Similarly, the prediction unit 22 further predicts the degree of possibility of consecutive lane changes C12, for example, based on predetermined parameters (at least one of relative speed V23 and relative distance L23) indicating the relative relationship between vehicle 2 and vehicle 3. In detail, the prediction unit 22 acquires information on the arrival time to the lane change destination (arrival time to the limit driving position at the lane change destination) when consecutive lane changes C12 are performed by vehicle 2, for example, based on such predetermined parameters. The prediction unit 22 then further predicts the degree of possibility of successive lane changes C12 based on the information on the arrival time, for example.

[0059] In this case, vehicles 1 and 3 each correspond to a specific example of "other vehicle" in one embodiment of the present disclosure.

[0060] (Operations and Effects) In the second modification, the same effects as those in the above-described embodiment can be obtained by basically operating in the same manner.

[0061] Furthermore, in particular, in this modification 2, the degree of possibility of consecutive lane changes C12 by vehicle 2 is further predicted taking into consideration the presence of other vehicles (vehicles 1, 3, etc.) traveling behind vehicle 2, resulting in the following: By further predicting the degree of possibility of such consecutive lane changes C12, it is possible to improve the prediction accuracy regarding the possibility of consecutive lane changes C12.

[0062] 3. 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.

[0063] 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.

[0064] Furthermore, in the above-described embodiments, various processing examples (such as the various prediction processes and driving assistance processes described above) have been specifically described. However, the present invention is not limited to the methods described in the above-described embodiments, and other methods may be used, for example. Specifically, in the above-described embodiments, an example has been described in which the vehicle 2 predicts whether or not it intends to proceed in the direction d2 based on the detection result of the lane change intention P2 of the vehicle 2. However, the present invention is not limited to this example. That is, for example, other methods may be used to predict whether or not it intends to proceed in the direction d2. Furthermore, in the above-described embodiments, an example has been described in which the vehicle 2 predicts whether or not it intends to proceed in the direction d2 by using traffic congestion information It for each travel lane, including the travel lanes L2 and L3. However, the present invention is not limited to this example. That is, the vehicle 2 may predict whether or not it intends to proceed in the direction d2 without using such traffic congestion information It.

[0065] 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.

[0066] Furthermore, in the above embodiment and the like, an example has been described in which the host vehicle, vehicle 1, is the "first vehicle" in an embodiment of the present disclosure, but this example is not limiting. That is, for example, a vehicle other than the host vehicle may be set as the "first vehicle" in an embodiment of the present disclosure. This is because the continuous lane change C12 by vehicle 2 is an act that poses a risk to vehicles traveling in the crossover travel lane (travel lane L3) and the destination travel lane (travel lane L1, etc.). Therefore, all vehicles present around vehicle 2 may be broadly set as the "first vehicle" in an embodiment of the present disclosure.

[0067] Additionally, in the above-described embodiment, the vehicle 1 is provided with a battery 12 as a power source. That is, in the above-described embodiment, the vehicle 1 is an electric vehicle (EV) or a hybrid electric vehicle (HEV), but the present invention is not limited to this example. That is, the vehicle 1 may be, for example, a gasoline-powered vehicle or a fuel-powered vehicle.

[0068] 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.

[0069] Furthermore, the various examples described above may be applied in any combination.

[0070] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0071] The present disclosure may also be configured as follows: (1) A driving assistance device comprising: a control unit configured to predict a likelihood of the second vehicle making a consecutive lane change from the second lane across the third lane toward the first lane, in a situation where a second vehicle is traveling in front of a first vehicle traveling in a first lane and the second lane is traveling in a second lane different from the first lane, one or more first route directions are defined on the first lane, and one or more second route directions different from the first route direction are defined on one or more third lanes located between the first lane and the second lane and on the second lane, respectively, wherein the control unit is configured to predict a likelihood of the second vehicle making the consecutive lane change based on a prediction result of whether the second vehicle intends to proceed in the second route direction. (2) The driving assistance device described in (1) above, wherein the control unit is configured to predict whether the second vehicle intends to proceed in the second route direction based on a detection result of an indication of an intention to change lanes from the second vehicle. (3) The driving assistance device according to (2), wherein the control unit is configured to predict, when an indication of an intention to change lanes by the second vehicle is detected, that there is a high possibility that the second vehicle has no intention to proceed in the second route direction. (4) The driving assistance device according to (3), wherein the control unit is further configured to predict whether or not the second vehicle has an intention to proceed in the second route direction by using congestion information for each lane including the second lane and the third lane. (5) The driving assistance device according to (4), wherein the control unit is configured to predict, when an indication of an intention to change lanes by the second vehicle is detected in a situation where the amount of congestion in the second lane is less than the amount of congestion in the third lane, that there is an even higher possibility that the second vehicle has no intention to proceed in the second route direction. (6) The driving assistance device according to any of (1) to (5), wherein the control unit is configured to predict, when it is predicted that the second vehicle has no intention to proceed in the second route direction, that there is a high possibility that the second vehicle will perform the continuous lane change.(7) The driving assistance device according to any one of (1) to (6), wherein, when it is predicted that the second vehicle is likely to perform the consecutive lane changes, the control unit is configured to further predict a destination lane to change to during the consecutive lane changes. (8) The driving assistance device according to (7), wherein, when there are a plurality of first route direction lanes, including the first lane, which are lanes for which the first route direction is specified, the control unit is configured to predict, as a destination lane to change to during the consecutive lane changes, a lane with the least amount of congestion among the plurality of first route direction lanes or a lane closest to the second lane. (9) The driving assistance device according to any one of (1) to (8), wherein the control unit is configured to further predict a degree of possibility of the consecutive lane changes of the second vehicle, taking into account the presence of another vehicle traveling behind the second vehicle. (10) The driving assistance device according to any one of (1) to (9) above, wherein the first route direction and the second route direction are defined by an intersection or a route branch point located ahead of the first vehicle and the second vehicle, respectively. (11) The driving assistance device according to any one of (1) to (10) above, wherein the control unit is configured to control driving assistance in a target vehicle by taking into account a prediction result regarding the successive lane changes in the second vehicle. (12) A vehicle equipped with the driving assistance device according to any one of (1) to (11) above. (13) The vehicle according to (12), wherein the vehicle is the first vehicle.(14) A driving assistance method, in a situation where a second vehicle is traveling in a second lane different from the first lane ahead of a first vehicle traveling in a first lane, one or more first course directions are defined on the first lane, and one or more second course directions different from the first course directions are defined on one or more third lanes located between the first lane and the second lane and on the second lane, respectively, the method includes predicting a possibility that the second vehicle will make a continuous lane change from the second lane across the third lane toward the first lane, wherein predicting the possibility of making the continuous lane change includes predicting the possibility that the second vehicle will make the continuous lane change based on a prediction result of whether or not the second vehicle intends to proceed in the second course direction.

[0072] The vehicle control unit 11 shown in FIGS. 1 and 2 can be implemented by circuitry 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 can be configured to perform all or some of the various functions of the vehicle control unit 11 shown in FIGS. 1 and 2 by reading instructions from at least one non-transitory, tangible computer-readable medium. Such medium can 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 memories can include DRAM and SRAM. Non-volatile memories can include ROM and NVRAM. An ASIC is an integrated circuit (IC) specialized to perform all or some of the various functions of the vehicle control unit 11 shown in FIGS. 1 and 2. The FPGA is an integrated circuit that is designed to be configurable after manufacture so as to execute all or part of the various functions of the vehicle control unit 11 shown in FIGS.

Claims

1. A driving assistance device comprising: a control unit configured to predict the possibility of the second vehicle making a continuous lane change from the second lane across the third lane toward the first lane, in a situation where a second vehicle is traveling in a second lane different from the first lane ahead of a first vehicle traveling in a first lane, one or more first course directions are defined on the first lane, and one or more second course directions different from the first course direction are defined on one or more third lanes located between the first lane and the second lane, and on the second lane, respectively; wherein the control unit is configured to predict the possibility of the second vehicle making the continuous lane change based on a prediction result of whether or not the second vehicle intends to proceed in the second course direction.

2. The driving assistance device of claim 1, wherein the control unit is configured to predict whether or not the second vehicle intends to proceed in the second direction based on the detection result of an indication of an intention to change lanes in the second vehicle.

3. The driving assistance device according to claim 2, wherein the control unit is configured to predict that there is a high possibility that the second vehicle has no intention of proceeding in the second direction when an indication of an intention to change lanes is detected in the second vehicle.

4. The driving assistance device according to claim 3, wherein the control unit is further configured to predict whether or not there is an intention to proceed in the second course direction by utilizing congestion information in each lane including the second lane and the third lane.

5. The driving assistance device according to claim 4, wherein the control unit is configured to predict that there is an even higher possibility that the second vehicle has no intention of proceeding in the second direction when an indication of an intention to change lanes is detected in the second vehicle in a situation where the amount of traffic congestion in the second lane is less than the amount of traffic congestion in the third lane.

6. A driving assistance device as described in any one of claims 1 to 5, wherein the control unit is configured to predict that the second vehicle is likely to make the consecutive lane changes when it is predicted that the second vehicle has no intention of proceeding in the second course direction.

7. A driving assistance device as described in any one of claims 1 to 5, wherein the control unit is configured to, when it is predicted that the second vehicle is likely to make the consecutive lane changes, further predict the destination of the lane changes during the consecutive lane changes.

8. The driving assistance device according to claim 7, wherein, when there are a plurality of first route direction lanes, including the first lane, which are lanes for which the first route direction is specified, the control unit is configured to predict, as the destination lane for the consecutive lane changes, the lane with the least amount of congestion among the plurality of first route direction lanes, or the lane closest to the second lane.

9. A driving assistance device as described in any one of claims 1 to 5, wherein the control unit is configured to further predict the degree of possibility of the second vehicle making successive lane changes, taking into account the presence of other vehicles traveling behind the second vehicle.

10. A driving assistance device as described in any one of claims 1 to 5, wherein the first route direction and the second route direction are determined by an intersection or a route branch point located ahead of the first vehicle and the second vehicle, respectively.

11. A driving assistance device as described in any one of claims 1 to 5, wherein the control unit is configured to control driving assistance in the target vehicle taking into account the prediction results regarding the successive lane changes in the second vehicle.

12. A vehicle equipped with a driving assistance device according to any one of claims 1 to 5.

13. The vehicle of claim 12, wherein said vehicle is said first vehicle.

14. A driving assistance method, in a situation where a second vehicle is traveling in a second lane different from the first lane ahead of a first vehicle traveling in a first lane, one or more first course directions are defined on the first lane, and one or more second course directions different from the first course direction are defined on one or more third lanes located between the first lane and the second lane, and on the second lane, respectively, the method includes predicting a possibility that the second vehicle will make a continuous lane change from the second lane across the third lane to the first lane, wherein predicting the possibility of making the continuous lane change includes predicting the possibility that the second vehicle will make the continuous lane change based on a prediction result of whether or not the second vehicle intends to proceed in the second course direction.

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