Driving assistance device, vehicle, and driving assistance method

Abstract

A driving assistance device according to one embodiment of the present disclosure comprises a control unit capable of predicting the likelihood of a second vehicle making a lane change to enter a first lane from a second lane adjacent to the first lane, ahead of a first vehicle traveling in the first lane. The control unit is capable of performing (1), (2), (3) below. (1) Acquire position information on each of a plurality of third vehicles traveling in the first lane, including the first vehicle, and size information on an inter-vehicular space ahead of the first vehicle (2) Determine, on the basis of the acquired position information and the acquired size information, whether or not the inter-vehicular space is an enterable space that the second vehicle can enter by making a lane change (3) In the case where the inter-vehicular space is an enterable space, predict the likelihood of the second vehicle entering the enterable space on the basis of the length of a waiting period that the second vehicle is expected to spend before starting a lane change into the enterable space or the length of a measured period having a predetermined correlation with the length of the waiting period

Description

Driving assistance device, vehicle, and driving assistance method

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

[0002] In recent years, development of automatic driving control technologies for vehicles such as automobiles that allow the vehicle to travel automatically without the need for driver operation has been progressing. Furthermore, various driving assistance devices that utilize this type of automatic driving control technology to perform various controls to assist the driver in driving have been proposed and are becoming generally put into practical use. Technologies related to such driving assistance devices are disclosed, for example, in Patent Documents 1 to 5.

[0003] International Publication No. WO2020 / 161512 Japanese Patent Application Laid-Open No. 2003-288691 Japanese Patent Application Laid-Open No. 5-517099 Japanese Patent Application Laid-Open No. 2020-160899 Japanese Patent Application Laid-Open No. 2021-060906

[0004] An information processing device according to a first aspect of the present disclosure includes a control unit capable of predicting the possibility that a second vehicle will change lanes from a second lane adjacent to the first lane to enter the first lane ahead of a first vehicle traveling in a first lane. The control unit is capable of performing the following (A1), (A2), and (A3): (A1) acquiring position information of each of a plurality of third vehicles traveling in the first lane, including the first vehicle, and size information of the inter-vehicle space ahead of the first vehicle; (A2) determining, based on the acquired position information and size information, whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes; and (A3) if the inter-vehicle space is an enterable space, predicting the possibility that the second vehicle will enter the enterable space based on the length of a waiting period that the second vehicle is expected to spend before starting to change lanes into the enterable space, or the length of an actual measurement period that has a predetermined correlation with the length of the waiting period.

[0005] A vehicle according to a second aspect of the present disclosure includes a control unit capable of predicting the possibility that a second vehicle will change lanes and enter the first lane from a second lane adjacent to the first lane ahead of a first vehicle traveling in a first lane. The control unit is capable of performing the following (B1), (B2), and (B3): (B1) acquiring position information of each of a plurality of third vehicles traveling in the first lane, including the first vehicle, and size information of the inter-vehicle space ahead of the first vehicle; (B2) determining, based on the acquired position information and size information, whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes; and (B3) if the inter-vehicle space is an enterable space, predicting the possibility that the second vehicle will enter the enterable space based on the length of a waiting period that the second vehicle is expected to spend before starting to change lanes into the enterable space, or the length of an actual measurement period that has a predetermined correlation with the length of the waiting period.

[0006] A driving assistance method according to a third aspect of the present disclosure is a method capable of predicting the possibility that a second vehicle will change lanes from a second lane adjacent to the first lane to enter the first lane ahead of a first vehicle traveling on a first lane. This driving assistance method includes the following steps (C1), (C2), and (C3): (C1) acquiring position information of each of a plurality of third vehicles traveling on the first lane, including the first vehicle, and size information of the inter-vehicle space ahead of the first vehicle; (C2) determining, based on the acquired position information and the acquired size information, whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes; and (C3) if the inter-vehicle space is an enterable space, predicting the possibility that the second vehicle will enter the enterable space based on the length of a waiting period that the second vehicle is expected to spend before starting to change lanes into the enterable space, or the length of an actual measurement period that has a predetermined correlation with the length of the waiting period.

[0007] A driving assistance device according to a fourth aspect of the present disclosure includes a control unit capable of predicting the possibility that a first vehicle traveling in a center lane of three lanes traveling in the same direction will change lanes and enter the right lane or the left lane of the three lanes. The control unit is capable of performing the following (D1) and (D2): (D1) acquiring number information of second vehicles traveling ahead of the first vehicle in the right lane and the left lane; and (D2) predicting the possibility that the first vehicle will enter the traveling lane based on the acquired number information.

[0008] 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.

[0009] FIG. 1 is a diagram illustrating an example of a schematic configuration of a cruise control system according to an embodiment of the present disclosure. FIG. 2 is a diagram illustrating an example of a lane change prediction procedure in the cruise control system of FIG. 1. FIG. 3 is a diagram illustrating an example of traffic conditions in steps S101 to S105 of FIG. 2. FIG. 4 is a diagram illustrating an example of traffic conditions in steps S106 to S108 of FIG. 2. FIG. 5 is a diagram illustrating an example of traffic conditions in step S109 of FIG. 2. FIG. 6 is a diagram illustrating a modified example of the lane change prediction procedure in the cruise control system of FIG. 1. FIG. 7 is a diagram illustrating an example of a prediction procedure subsequent to FIG. 6. FIG. 8 is a diagram illustrating an example of traffic conditions in steps S201 to S205 of FIG. 6. FIG. 9 is a diagram illustrating an example of traffic conditions in steps S206 to S208 of FIG. 7. FIG. 10 is a diagram illustrating an example of traffic conditions in step S209 of FIG. 7. FIG. 11 is a diagram illustrating a hypothetical example of traffic conditions. FIG. 12 is a diagram illustrating a hypothetical example of traffic conditions subsequent to FIG. 11.

[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. Background> In recent years, development of automatic driving control technologies for vehicles such as automobiles that allow vehicles to travel automatically without the need for driver operation has been progressing. In addition, various proposals have been made for driving assistance devices that use this type of automatic driving control technology to perform various controls to assist the driver in driving operations, and these devices are gradually being put into practical use.

[0012] Some conventional driving assistance devices are equipped with a lane-keeping driving control function that constantly recognizes the vehicle's surroundings using various sensor devices and keeps the vehicle traveling along the lane it is currently traveling in based on various acquired information data. While the vehicle is automatically traveling using the lane-keeping driving control function, a vehicle traveling in an adjacent lane may change lanes in front of the vehicle. In this case, depending on the timing of the lane change, there is a risk that the vehicle may collide with the vehicle that has changed lanes. To safely avoid such a risk, it is important to predict whether the vehicle traveling in the adjacent lane is about to change lanes and perform driving control in accordance with the prediction. Technologies for predicting lane changes are disclosed, for example, in Patent Documents 1 to 5.

[0013] In the inventions described in Patent Documents 1 and 2, it is predicted that the longer the inter-vehicle space immediately in front of the host vehicle, the higher the possibility that a vehicle in an adjacent lane will change lanes. However, even if the inter-vehicle space immediately in front of the host vehicle becomes longer, it is not necessarily the case that the vehicle in the adjacent lane will change lanes, so there is a possibility that unnecessary driving control in preparation for a lane change will occur frequently.

[0014] In the invention described in Patent Document 3, if the speed of the host vehicle and that of a vehicle in an adjacent lane continue to be approximately the same for a predetermined period of time, it is predicted that the possibility of the vehicle in the adjacent lane changing lanes increases. However, even if the speed of the host vehicle and that of a vehicle in an adjacent lane continue to be approximately the same for a predetermined period of time, it is not necessarily the case that the vehicle in the adjacent lane will change lanes, so there is a possibility that unnecessary driving control in preparation for a lane change will occur frequently.

[0015] The invention described in Patent Document 4 predicts that the possibility of a lane change becomes high when a traffic jam occurs in an adjacent lane and a vehicle is stopped due to the traffic jam for a predetermined period of time. However, this invention is based on the premise that a vehicle in the adjacent lane is stopped due to the traffic jam, and does not take into account lane changes by a vehicle traveling in the adjacent lane.

[0016] The invention described in Patent Document 5 predicts the possibility of a lane change based on the number of vehicles behind the target vehicle in the lanes on either side of the lane the target vehicle is traveling in. However, when changing lanes, it is difficult for the driver to grasp the number of vehicles behind while driving, and it is unclear to what extent there is a correlation between the number of vehicles behind while driving and the actual possibility of changing lanes. As a result, there is a possibility that unnecessary driving control in preparation for a lane change will occur frequently.

[0017] As described above, conventional inventions have a problem in that unnecessary driving control in preparation for lane changes may occur frequently. Therefore, the inventors of the present application have intensively studied and come up with a technology that can predict the possibility of a lane change based on traffic conditions that have a high correlation with the psychological state that makes the driver want to change lanes. Below, we will explain the background of this newly conceived technology by giving hypothetical examples of traffic conditions.

[0018] FIG. 11 illustrates a hypothetical example of a traffic situation. A vehicle (host vehicle) 100x is traveling on a road with two lanes on each side. This road is composed of a driving lane L1 in which the vehicle 100x is traveling and an opposite lane L2 that runs alongside the driving lane L1 via a center line. Two lanes (driving lanes L3 and L4) are provided in the driving lane L1. The driving lane L3 is a so-called overtaking lane, and a driving lane L4 is provided between the center line and the driving lane L3. The vehicle 100x is traveling in the driving lane L3, and a vehicle (lane-changing vehicle) 100y that will later change lanes from the driving lane L4 to the driving lane L3 is traveling in the driving lane L4. The driving lane L4 is congested, while the driving lane L3 is clear, and the vehicle 100y is in a situation where it wants to change lanes from the driving lane L4 to the driving lane L3.

[0019] Assume that vehicle 100y was attempting to change lanes but failed to change lanes into inter-vehicle space Sa where a lane change is possible, and is still traveling in driving lane L4. At this time, the driver of vehicle 100y needs to wait in driving lane L4 until the next inter-vehicle space Sb where a lane change is possible arrives. During this waiting period, the driver of vehicle 100y needs to continue paying attention to driving lane L3 in order to detect the arrival of the next inter-vehicle space Sb early.

[0020] The longer the driver of vehicle 100y continues traveling in lane L3 to detect the approaching inter-vehicle space Sb (hereinafter referred to as the "waiting time"), the more irritated he or she becomes and the less likely he or she is to pay attention to the surrounding traffic conditions. As a result, the driver of vehicle 100y is more likely to make a recognition error and reflexively change lanes when he or she detects inter-vehicle space Sb. Such reflexive lane changes may pose a danger to vehicles traveling in lane L3. In particular, if vehicle (host vehicle) 100x is the vehicle that forms the rear end of inter-vehicle space Sb, as shown in FIG. 12, there is a high risk that vehicle 100y will collide with vehicle 100x. Therefore, the inventors of the present application focused on the length of the waiting period, which is highly correlated with the psychological state in which a driver is prone to making a recognition error, and conceived of predicting the likelihood of a lane change based on the length of the waiting period. A cruise control system for achieving this is described in detail below.

[0021] 2. Embodiments> [Configuration Example] Fig. 1 shows a schematic configuration example of a cruise control system 1 according to an embodiment of the present disclosure. As shown in Fig. 1, the cruise control system 1 includes cruise control devices 10 mounted on a plurality of vehicles, respectively, and a control device 200 provided in a network environment NW to which the plurality of cruise control devices 10 are connected via wireless communication. The cruise control device 10 corresponds to a specific example of a "driving assistance device" according to an embodiment of the present disclosure.

[0022] The control device 200 sequentially integrates and updates the road map information transmitted from the cruise control devices 10 of the vehicles, and transmits the updated road map information to the vehicles. The control device 200 includes, for example, a road map information integration ECU 201 and a transceiver 202.

[0023] The road map boundary information integration ECU 201 integrates road map information collected from multiple vehicles via the transceiver 202, and sequentially updates road map information surrounding the vehicle on the road. The road map information may be, for example, a dynamic map, and includes static information and quasi-static information that mainly constitute road information, and quasi-dynamic information and dynamic information that mainly constitute traffic information.

[0024] Static information includes information that requires updates within one month, such as road and road structure information, lane information, road surface information, and permanent traffic restriction information. Semi-static information includes information that requires updates within one hour, such as traffic restriction information due to road construction or events, wide-area weather information, and congestion forecasts. Semi-dynamic information includes information that requires updates within one minute, such as actual traffic congestion and travel restrictions at the time of observation, temporary traffic obstructions such as fallen objects and obstacles, actual accident conditions, and narrow-area weather information. Dynamic information includes information that requires updates in units of one second, such as information transmitted and exchanged between mobile units, information on currently displayed traffic signals, information on pedestrians and bicycles at intersections, and information on vehicles traveling on the road. Such road map information is maintained and updated periodically until the next information is received from each vehicle, and the updated road map information is appropriately transmitted to each vehicle via the transceiver 202.

[0025] The cruise control device 10 has a cruise environment recognition unit 11 and a locator unit 12 as units for recognizing the cruise environment around the vehicle. The cruise control device 10 also has a cruise control unit (hereinafter referred to as the "cruise_ECU") 22, an engine control unit (hereinafter referred to as the "E / G_ECU") 23, a power steering control unit (hereinafter referred to as the "PS_ECU") 24, and a brake control unit (hereinafter referred to as the "BK_ECU") 25. These control units 22 to 25 are connected to the cruise environment recognition unit 11 and the locator unit 12 via an in-vehicle communication line such as a Controller Area Network (CAN).

[0026] The travel_ECU 22 controls the vehicle according to, for example, a driving mode. Examples of the driving modes include a manual driving mode and a driving control mode. The manual driving mode is a driving mode that requires the driver to maintain steering, and the host vehicle is driven according to driving operations such as steering, accelerator, and brake operations by the driver. The driving control mode is a driving mode that supports the driver in driving operations by the driver to increase the safety of pedestrians and other vehicles around the vehicle (host vehicle). In the driving control mode, for example, when the vehicle (host vehicle) approaches an intersection and a traffic light at the intersection changes from green to yellow and then to red, the travel_ECU 22 controls the vehicle (host vehicle) to stop at a stop line near the intersection. Detailed processing in the driving control mode will be described later.

[0027] A throttle actuator 27 is connected to the output side of the E / G_ECU 23. This throttle actuator 27 opens and closes a throttle valve of an electronically controlled throttle provided in a throttle body of the engine, and generates a desired engine output by opening and closing the throttle valve in response to a drive signal from the E / G_ECU 23 to adjust the intake air flow rate.

[0028] An electric power steering motor 28 is connected to the output side of the PS_ECU 24. This electric power steering motor 28 applies steering torque to the steering mechanism by the rotational force of the motor, and in autonomous driving, the electric power steering motor 28 is controlled by a drive signal from the PS_ECU 24 to perform lane keeping control, which keeps the vehicle traveling in the current lane, and lane change control, which moves the vehicle to an adjacent lane (lane change control for overtaking control, etc.).

[0029] A brake actuator 29 is connected to the output side of the BK_ECU 25. This brake actuator 29 adjusts the brake hydraulic pressure supplied to the brake wheel cylinders provided on each wheel, and when the brake actuator 29 is driven by a drive signal from the BK_ECU 25, the brake wheel cylinders generate braking force on each wheel, forcibly slowing down the vehicle.

[0030] The driving environment recognition unit 11 is fixed, for example, to the center of the upper part of the front interior of the vehicle. The driving environment recognition unit 11 has an in-vehicle camera (stereo camera) consisting of a main camera 11a and a sub-camera 11b, an image processing unit (IPU) 11c, and a driving environment detection unit 11d.

[0031] The main camera 11a and the sub-camera 11b are autonomous sensors that sense the real space around the vehicle. The main camera 11a and the sub-camera 11b are, for example, arranged at symmetrical positions on either side of the center of the vehicle in the width direction, and capture stereo images of the area in front of the vehicle from different viewpoints.

[0032] The IPU 11c generates a distance image based on a pair of stereo images of the area in front of the vehicle obtained by capturing images with the main camera 11a and the sub-camera 11b, and calculates the amount of displacement between the positions of corresponding objects.

[0033] The driving environment detection unit 11d, for example, determines lane markings that divide the road around the vehicle based on the distance image received from the IPU 11c. The driving environment detection unit 11d further determines, for example, the road curvature [1 / m] of the markings that divide the left and right sides of the roadway (driving lane) on which the vehicle is traveling, and the width between the left and right markings (vehicle width). The driving environment detection unit 11d further performs, for example, predetermined pattern matching on the distance image to detect lanes and three-dimensional objects such as structures that exist around the vehicle.

[0034] Here, the detection of a three-dimensional object by the driving environment detection unit 11d includes, for example, detecting the type of the three-dimensional object, the distance to the three-dimensional object, the speed of the three-dimensional object, and the relative speed between the three-dimensional object and the vehicle (host vehicle). Examples of three-dimensional objects to be detected include traffic lights, intersections, road signs, stop lines, other vehicles, and pedestrians. The driving environment detection unit 11d outputs information about the detected three-dimensional objects to the driving_ECU 22, for example.

[0035] The locator unit 12 estimates the vehicle's position (host vehicle position) on a road map and includes a locator calculation unit 13 that estimates the host vehicle position. Sensors required for estimating the vehicle's position (host vehicle position) are connected to the input side of the locator calculation unit 13. Examples of such sensors include an acceleration sensor 14, a vehicle speed sensor 15, a gyro sensor 16, and a GNSS receiver 17. The acceleration sensor 14 detects the longitudinal acceleration of the vehicle. The vehicle speed sensor 15 detects the vehicle's speed. The gyro sensor 16 detects the vehicle's angular velocity or angular acceleration. The GNSS receiver 17 receives positioning signals transmitted from multiple positioning satellites. The locator calculation unit 13 is also connected to a transceiver 18 that transmits and receives information to and from the control device 200 and other vehicles.

[0036] A high-precision road map database 19 is also connected to the locator calculation unit 13. The high-precision road map database 19 is a large-capacity storage medium such as an HDD, and stores high-precision road map information (dynamic map). This high-precision road map information, like the road map information included in the road map information integration_ECU 201, mainly includes static information and quasi-static information constituting road information, and quasi-dynamic information and dynamic information constituting traffic information.

[0037] The locator calculation unit 13 includes, for example, a map information acquisition unit 13a, a vehicle position estimation unit 13b, and a driving environment recognition unit 13c.

[0038] The vehicle position estimation unit 13b acquires the position coordinates of the vehicle (host vehicle) based on the positioning signal received by the GNSS receiver 17. The vehicle position estimation unit 13b also estimates the host vehicle's position on a road map by map-matching the acquired position coordinates with route map information. The map information acquisition unit 13a acquires map information of a predetermined range including the vehicle (host vehicle) from map information stored in the high-precision road map database 19, based on the position coordinates of the vehicle (host vehicle) acquired by the vehicle position estimation unit 13b.

[0039] In an environment where valid positioning signals from positioning satellites cannot be received due to reduced sensitivity of the GNSS receiver 17, such as when driving inside a tunnel, the vehicle position estimation unit 13b switches to autonomous navigation, which estimates the vehicle's position based on the vehicle speed detected by the vehicle speed sensor 15, the angular velocity detected by the gyro sensor 16, and the longitudinal acceleration detected by the acceleration sensor 14, and estimates the vehicle's position on a road map.

[0040] As described above, the vehicle position estimation unit 13b estimates the position of the vehicle (subject vehicle position) on the road map based on the positioning signal received by the GNSS receiver 17 or information detected by the gyro sensor 16, etc., and then determines the road type, etc. of the road on which the vehicle (subject vehicle) is traveling based on the estimated subject vehicle position on the road map.

[0041] The driving environment recognition unit 13c updates the road map information stored in the high-precision road map database 19 to the latest version using road map information acquired through external communication (roadside-to-vehicle communication and vehicle-to-vehicle communication) via the transceiver 18. This information update is performed not only on static information but also on quasi-static information, quasi-dynamic information, and dynamic information. As a result, the road map information includes road information and traffic information acquired through communication with the outside of the vehicle, and information on moving bodies such as vehicles traveling on roads is updated in approximately real time.

[0042] The driving environment recognition unit 13c verifies road map information based on the driving environment information recognized by the driving environment recognition unit 11, and updates the road map information stored in the high-precision road map database 19 to the latest state. This information update is performed not only on static information, but also on quasi-static information, quasi-dynamic information, and dynamic information. As a result, information on moving objects such as vehicles traveling on roads recognized by the driving environment recognition unit 11 is updated in real time.

[0043] The road map information thus updated is then transmitted to the control device 200 and vehicles around the vehicle (host vehicle) by road-to-vehicle communication and vehicle-to-vehicle communication via the transceiver 18. Furthermore, the driving environment recognition unit 13c outputs, from the updated road map information, map information of a predetermined range including the host vehicle position estimated by the vehicle position estimation unit 13b, together with the host vehicle position (vehicle position information), to the driving_ECU 22.

[0044] Next, the travel_ECU 22 will be described in detail.

[0045] Fig. 2 shows an example of a procedure for predicting a lane change in the cruise control system 1. Fig. 3 shows an example of traffic conditions in steps S101 to S105 in Fig. 2. Fig. 4 shows an example of traffic conditions in steps S106 to S108 in Fig. 2. Fig. 5 shows an example of traffic conditions in step S109 in Fig. 2.

[0046] In FIG. 3 , vehicle (host vehicle) 100a is traveling on a road with two lanes in each direction. Vehicle 100a corresponds to a specific example of a "first vehicle" according to an embodiment of the present disclosure. This two-lane road is composed of a two-lane driving lane L1 in which vehicle 100a is traveling and an opposite lane L2 that is provided along driving lane L1 with a center line interposed therebetween. Driving lane L1 has two lanes (driving lanes L3 and L4). Driving lane L3 corresponds to a specific example of a "first lane" according to an embodiment of the present disclosure. Driving lane L4 corresponds to a specific example of a "second lane" according to an embodiment of the present disclosure. Driving lane L3 is a so-called passing lane, and driving lane L4 is provided between the center line and driving lane L3. Vehicle 100a is traveling in driving lane L3, and a vehicle that will later change lanes from driving lane L4 to driving lane L3 is traveling in driving lane L4. The driving lane L4 is congested, and a vehicle traveling in the driving lane L4 is in a situation where it wants to change lanes from the driving lane L4 to the driving lane L3.

[0047] A stereo camera provided on vehicle 100a captures images of the area ahead of vehicle 100a and outputs the resulting stereo image to IPU 11c. The stereo image includes at least a plurality of vehicles traveling ahead of vehicle 100a in traveling lane L1. At this time, traveling environment detection unit 11d can directly detect inter-vehicle space Si in traveling lane L3. At this time, traveling_ECU 22 may acquire position information and length information of inter-vehicle space Si based on inter-vehicle space Si detected by traveling environment detection unit 11d and map information and the host vehicle position acquired from traveling environment recognition unit 13c.

[0048] In road conditions where the inter-vehicle space Si cannot be visually recognized, the driving environment detection unit 11d is likely to be unable to detect the inter-vehicle space Si in the stereo image. Anticipating such a situation, the driving_ECU 22 has a function that enables it to estimate the inter-vehicle space Si even when it is unable to acquire information on the inter-vehicle space Si from the driving environment detection unit 11d. An example of a method for estimating the inter-vehicle space Si will be described below.

[0049] First, the stereo camera acquires stereo images and outputs them to the IPU 11c. The IPU 11c generates a distance image based on the stereo images acquired by the stereo camera and outputs the image to the driving environment detection unit 11d. The driving environment detection unit 11d performs predetermined pattern matching on the distance image generated by the IPU 11c, and detects each vehicle 100b traveling ahead of the vehicle 100a in the driving lane L1. Note that, among the vehicles 100b at this time, each vehicle traveling in the driving lane L3 corresponds to a specific example of "multiple third vehicles" according to an embodiment of the present disclosure.

[0050] At this time, if each vehicle 100b is successfully detected, the driving environment detection unit 11d calculates the distance di from the vehicle 100a to each vehicle 100b. The driving environment detection unit 11d calculates the distance di from the vehicle 100a to each vehicle 100b, for example, based on the distance image. The driving environment detection unit 11d outputs the calculated distance di to the driving_ECU 22 in association with the identifier of each vehicle 100b.

[0051] The traveling_ECU 22 acquires, from the traveling environment recognition unit 13c, map information of a predetermined range including the host vehicle position estimated by the vehicle position estimation unit 13b and the host vehicle position. Note that the host vehicle position at this time corresponds to a specific example of "position information of the first vehicle" according to an embodiment of the present disclosure. The traveling_ECU 22 matches the vehicle 100b based on the distance di and the identifier of the vehicle 100b acquired from the traveling environment detection unit 11d and the map information and the host vehicle position acquired from the traveling environment recognition unit 13c.

[0052] Specifically, the traveling_ECU 22 determines whether the map information acquired from the traveling environment recognition unit 13c includes an object corresponding to the vehicle 100b detected by the traveling environment recognition unit 13c. For example, the traveling_ECU 22 acquires, from the map information acquired from the traveling environment recognition unit 13c, a position (xbi, ybi) that is a distance di from the host vehicle position as the position of the vehicle 100b acquired by the stereo camera. Here, xbi is longitude information in the road map information stored in the high-precision road map database 19. ybi is latitude information in the road map information stored in the high-precision road map database 19.

[0053] Next, the traveling_ECU 22 determines whether an object corresponding to the vehicle 100b is included within a predetermined distance (threshold value) from the position (xbi, ybi) of the vehicle 100b in the map information acquired from the traveling-environment recognition unit 13c. For example, when the traveling_ECU 22 detects an object corresponding to the vehicle 100b within the above-mentioned range in the map information acquired from the traveling-environment recognition unit 13c, it acquires the position (Xbi, Xbi) as position information Di of the vehicle 100b (step S101). Note that, among the position information Di at this time, the position information of the vehicle 100b traveling in the traveling lane L3 corresponds to a specific example of "position information of the third vehicle" according to an embodiment of the present disclosure.

[0054] When the vehicle 100b is matched, the traveling_ECU 22 acquires the inter-vehicle space Si between the two adjacent vehicles 100b on the traveling lane L3 based on the map information acquired from the traveling-environment recognition unit 13c (step S102). Specifically, the traveling_ECU 22 calculates the inter-vehicle space Si using the positions (Xbi, Xbi) of the two adjacent vehicles 100b.

[0055] On the other hand, if matching of the vehicle 100b has not been possible, the travel_ECU 22 determines whether the inter-vehicle space Si has been calculated in the past. If the inter-vehicle space Si has been calculated in the past, the travel_ECU 22 regards the previously calculated inter-vehicle space Si as the current inter-vehicle space Si. If the inter-vehicle space Si has not been calculated in the past, the travel_ECU 22 ends the calculation of the inter-vehicle space Si.

[0056] Next, the traveling_ECU 22 determines whether the inter-vehicle space Si is equal to or greater than the threshold value Sth (step S103). If the inter-vehicle space Si is less than the threshold value Sth (step S103; N), the traveling_ECU 22 executes step S101 again. On the other hand, if the inter-vehicle space Si is equal to or greater than the threshold value Sth (step S103; Y), the traveling_ECU 22 acquires the congestion degree J of the traveling lane L4 based on the position information Di of each vehicle 100b traveling on the traveling lane L4 (step S104). For example, the traveling_ECU 22 determines the congestion degree J of the traveling lane L4 by dividing the number of vehicles 100b present on the traveling lane L4 between the vehicle (host vehicle) 100a and a position a predetermined distance (distance Do) ahead of the vehicle (host vehicle) 100a by the distance Do.

[0057] Next, the travel_ECU 22 determines whether the congestion level J is equal to or greater than a threshold value Jth (step S105). If the congestion level J is less than the threshold value Jth (step S105; N), the travel_ECU 22 executes step S101 again. On the other hand, if the congestion level J is equal to or greater than the threshold value Jth (step S105; Y), the travel_ECU 22 determines, for example, as shown in FIG. 4, the vehicle 100b that can enter the inter-vehicle space Si (entrance-enabled space SSi) that satisfies Si≧Sth as the vehicle 100c to be monitored (step S106). The entry-enabled space SSi corresponds to a specific example of an "entrance-enabled space" according to an embodiment of the present disclosure. The monitored vehicle 100c corresponds to a specific example of a "second vehicle" according to an embodiment of the present disclosure.

[0058] In this way, the travel_ECU 22 determines whether the inter-vehicle space Si is an enterable space SSi based on the position information of the vehicle (host vehicle) 100a, the position information Di of each vehicle 100b, and the size information of the inter-vehicle space SSi. If the inter-vehicle space SSi is an enterable space SSi, the travel_ECU 22 executes the following process.

[0059] The travel_ECU 22 predicts a waiting period Tai of the monitored vehicle 100c, or measures an actual measurement period Tbi having a predetermined correlation with the waiting period Tai, based on information acquired while repeatedly executing the above-described processes (e.g., steps S101 to S106) (step S107). The waiting period Tai corresponds to a waiting period predicted to be spent by the monitored vehicle 100c before starting a lane change into the entry space SSi. If the monitored vehicle 100c continues traveling on the driving lane L4 without changing lanes into the entry space SSi, the waiting period Tai corresponds to a waiting period predicted to be spent before starting a lane change into the next entry space SSi. The waiting period Tai can be predicted based on, for example, the distance between the monitored vehicle 100c and the entry space SSi, the speed of the monitored vehicle 100c, and the speed of the vehicle 100b at the end of the entry space SSi.

[0060] The start timing of the waiting time Tai and the actual measurement period Tbi may include various timings, as shown below. For example, suppose that before the determination in step S103, the inter-vehicle space Si was an accessible space SSi into which the monitored vehicle 100c could enter by changing lanes, but the monitored vehicle 100c did not change lanes to the driving lane L3 (hereinafter referred to as "incident A"). In this case, the start timing of the waiting time Tai and the actual measurement period Tbi corresponds to, for example, the timing when incident A occurred. Note that the vehicle 100b at the rear end of the accessible space SSi at this time corresponds to a specific example of a "fourth vehicle" according to an embodiment of the present disclosure. Furthermore, for example, suppose that before the determination in step S103, the monitored vehicle 100c encountered traffic congestion in the driving lane L4 (hereinafter referred to as "incident B"). In this case, the start timing of the waiting time Tai and the measurement period Tbi may correspond to the timing when the incident B occurred, for example.

[0061] The end timing of the actual measurement period Tbi is, for example, the timing when the determination in step S108 starts. The timing when the determination in step S108 starts is a predetermined period before the timing when the monitored vehicle 100c actually starts changing lanes. The end timing of the actual measurement period Tbi is not limited to the timing when the determination in step S108 starts.

[0062] Next, the travel_ECU 22 predicts the possibility that the monitored vehicle 100c will enter the accessible space SSi based on the waiting period Tai or the actual measurement period Tbi. Specifically, the travel_ECU 22 determines whether the waiting period Tai or the actual measurement period Tbi is equal to or greater than the threshold value Tth (step S108). As a result, if the waiting period Tai or the actual measurement period Tbi is less than the threshold value Tth (step S108; N), the travel_ECU 22 executes step S101 again. On the other hand, if the waiting period Tai or the actual measurement period Tbi is equal to or greater than the threshold value Tth (step S108; Y), the travel_ECU 22 recognizes the vehicle 100c that satisfies Tai≧Tth or Tbi≧Tth as a vehicle 100d that is at high risk of changing lanes, as shown in FIG. 5 (step S109).

[0063] Thereafter, the cruise control device 10 of the vehicle (host vehicle) 100a executes cruise control assuming a lane change of the vehicle 100d (step S110). In this manner, the cruise control system 1 executes lane change prediction and cruise control.

[0064] [Effects] Next, effects of the cruise control system 1 according to one embodiment of the present disclosure will be described.

[0065] In this embodiment, when the inter-vehicle space Si is an enterable space SSi, the possibility that the monitored vehicle 100c will enter the enterable space SSi is predicted based on the length of the waiting period Tai spent by the monitored vehicle 100c until it starts changing lanes into the enterable space SSi, or the length of the actual measurement period Tbi.

[0066] Here, the driver of the monitored vehicle 100c continues to pay attention to the driving lane L3 during the waiting period Ti in order to find the entry space SSi. Therefore, the longer the waiting period Tai, the more irritated the driver of the monitored vehicle 100c becomes, and the less likely he or she is to pay attention to the surrounding traffic conditions. As a result, the driver of the monitored vehicle 100c is more likely to make a recognition error and reflexively change lanes when he or she finds the inter-vehicle space Sb. Therefore, the longer the waiting period Tai or the actual measurement period Tbi, the more likely the monitored vehicle 100c is to change lanes.

[0067] In this manner, in this embodiment, the possibility that the monitored vehicle 100c will enter the entry space SSi is predicted based on the length of the waiting period Tai or the length of the actual measurement period Tbi, which are highly correlated with the psychological state of the driver of the monitored vehicle 100c that makes the driver prone to misperception. This makes it possible to reduce the possibility of unnecessary driving control in preparation for lane changes occurring frequently.

[0068] In this embodiment, if the start timing of the waiting period Tai or the actual measurement period Tbi corresponds to the occurrence of the above-mentioned incident A, in incident A, the driver of the monitored vehicle 100c is in a psychological state where he or she misses a lane change and wants to change lanes quickly, and is also in a psychological state where there is a high possibility of a recognition error. Therefore, measurement of the waiting period Tai or the actual measurement period Tbi is started at the occurrence of incident A, and the possibility that the monitored vehicle 100c will enter the entry space SSi is predicted based on the waiting period Tai obtained by prediction or the actual measurement period Tbi obtained by actual measurement. This reduces the possibility of unnecessary driving control occurring frequently in preparation for lane changes.

[0069] In this embodiment, the start timing of the waiting period Tai or the actual measurement period Tbi corresponds to the occurrence of the above-mentioned event B. In event B, the driver of the monitored vehicle 100c is in a psychological state where he or she wants to change lanes quickly due to frustration at the traffic jam, and is in a psychological state where recognition errors are likely to occur. Therefore, measurement of the waiting period Tai or the actual measurement period Tbi is started at the occurrence of event B, and the possibility that the monitored vehicle 100c will enter the entry space SSi is predicted based on the waiting period TiTai obtained by prediction or the actual measurement period Tbi obtained by actual measurement. This reduces the possibility of unnecessary driving control occurring frequently in preparation for lane changes.

[0070] 3. Modifications The present disclosure has been described above by giving embodiments, but the present disclosure is not limited to these embodiments and various modifications are possible.

[0071] Fig. 6 shows a modified example of the procedure for predicting a lane change in the cruise control system 1. Fig. 7 shows an example of the prediction procedure following Fig. 6. Fig. 8 shows an example of traffic conditions in steps S201 to S205 in Fig. 6. Fig. 9 shows an example of traffic conditions in steps S206 to S208 in Fig. 7. Fig. 10 shows an example of traffic conditions in step S209 in Fig. 7.

[0072] In FIG. 8 , vehicle (host vehicle) 100a is traveling on a road with three lanes on each side. This three-lane road is composed of a three-lane driving lane L1 on which vehicle 100a is traveling and an opposite lane (not shown) that runs parallel to driving lane L1 via a center line. Driving lane L1 has three lanes (driving lanes L3, L4, and L5) that run in the same direction of travel. Driving lanes L4 and L5 are so-called passing lanes, driving lane L4 is a center lane, and driving lane L3 is located between the center line and driving lane L4. Driving lane L3 corresponds to a specific example of a "left lane" according to an embodiment of the present disclosure. Driving lane L5 corresponds to a specific example of a "right lane" according to an embodiment of the present disclosure.

[0073] Vehicle 100a is traveling in driving lane L3, and a vehicle is traveling in driving lane L4 that will later change lanes from driving lane L4 to driving lane L3 or driving lane L5. Driving lane L4 is congested, and the vehicle traveling in driving lane L4 is in a situation where it wants to change lanes from driving lane L4 to driving lane L3 or driving lane L5.

[0074] A stereo camera provided on vehicle 100a captures images of the area ahead of vehicle 100a and outputs the resulting stereo image to IPU 11c. The stereo image includes at least a plurality of vehicles traveling ahead of vehicle 100a in traveling lane L1. At this time, traveling environment detection unit 11d can directly detect inter-vehicle spaces Si in traveling lanes L3, L4, and L5. At this time, traveling_ECU 22 may acquire position information and length information of inter-vehicle spaces Si based on the inter-vehicle spaces Si detected by traveling environment detection unit 11d and the map information and vehicle position acquired from traveling environment recognition unit 13c.

[0075] In road conditions where the inter-vehicle space Si cannot be visually recognized, the driving environment detection unit 11d is likely to be unable to detect the inter-vehicle space Si in the stereo image. Anticipating such a situation, the driving_ECU 22 has a function that enables it to estimate the inter-vehicle space Si even when it is unable to acquire information on the inter-vehicle space Si from the driving environment detection unit 11d. An example of a method for estimating the inter-vehicle space Si will be described below.

[0076] First, the stereo camera acquires stereo images and outputs them to the IPU 11c. The IPU 11c generates a distance image based on the stereo images acquired by the stereo camera and outputs the distance image to the driving environment detection unit 11d. The driving environment detection unit 11d performs predetermined pattern matching on the distance image generated by the IPU 11c, and detects each vehicle 100b traveling ahead of the vehicle 100a in the driving lane L1.

[0077] At this time, if each vehicle 100b is successfully detected, the driving environment detection unit 11d calculates the distance di from the vehicle 100a to each vehicle 100b. The driving environment detection unit 11d calculates the distance di from the vehicle 100a to each vehicle 100b, for example, based on the distance image. The driving environment detection unit 11d outputs the calculated distance di to the driving_ECU 22 in association with the identifier of each vehicle 100b.

[0078] The travel_ECU 22 acquires, from the travel environment recognition unit 13 c, map information of a predetermined range including the host vehicle position estimated by the vehicle position estimation unit 13 b, and the host vehicle position. The travel_ECU 22 performs matching of the vehicle 100 b based on the distance di and the identifier of the vehicle 100 b acquired from the travel environment detection unit 11 d and the map information and the host vehicle position acquired from the travel environment recognition unit 13 c.

[0079] Specifically, the traveling_ECU 22 determines whether or not the map information acquired from the traveling environment recognition unit 13 c includes an object corresponding to the vehicle 100 b detected by the traveling environment recognition unit 13 c. For example, the traveling_ECU 22 acquires, from the map information acquired from the traveling environment recognition unit 13 c, a position (xbi, ybi) that is a distance di from the host vehicle position as the position of the vehicle 100 b acquired by the stereo camera.

[0080] Next, the traveling_ECU 22 determines whether or not an object corresponding to the vehicle 100b is included within a predetermined distance (threshold value) from the position (xbi, ybi) of the vehicle 100b in the map information acquired from the traveling-environment recognition unit 13c. For example, when the traveling_ECU 22 detects an object corresponding to the vehicle 100b within the above-mentioned range in the map information acquired from the traveling-environment recognition unit 13c, it acquires the position (Xbi, Xbi) of the vehicle 100b as position information Di of the vehicle 100b (step S201).

[0081] If the vehicle 100b is matched, the travel_ECU 22 acquires the inter-vehicle space Si between the two adjacent vehicles 100b on the travel lanes L3 and L5 based on the map information acquired from the travel-environment recognition unit 13c (step S202). Specifically, the travel_ECU 22 calculates the inter-vehicle space Si using the positions (Xbi, Xbi) of the two adjacent vehicles 100b.

[0082] On the other hand, if matching of the vehicle 100b has not been possible, the travel_ECU 22 determines whether the inter-vehicle space Si has been calculated in the past. If the inter-vehicle space Si has been calculated in the past, the travel_ECU 22 regards the previously calculated inter-vehicle space Si as the current inter-vehicle space Si. If the inter-vehicle space Si has not been calculated in the past, the travel_ECU 22 ends the calculation of the inter-vehicle space Si.

[0083] Next, the traveling_ECU 22 determines whether the inter-vehicle space Si is equal to or greater than the threshold value Sth (step S203). If the inter-vehicle space Si is less than the threshold value Sth (step S203; N), the traveling_ECU 22 executes step S201 again. On the other hand, if the inter-vehicle space Si is equal to or greater than the threshold value Sth (step S203; Y), the traveling_ECU 22 acquires the congestion levels J3, J4, and J5 (information on the number of vehicles 100b) of the traveling lane L1 based on the position information Di of each vehicle 100b traveling on the traveling lanes L3, L4, and L5 (step S204).

[0084] For example, the traveling_ECU 22 determines the congestion degree J3 of the traveling lane L3 by dividing the number of vehicles 100b that exist between the vehicle (host vehicle) 100a and a position a predetermined distance (distance Do) ahead of the vehicle (host vehicle) 100a in the traveling lane L3 by the distance Do. For example, the traveling_ECU 22 determines the congestion degree J4 of the traveling lane L4 by dividing the number of vehicles 100b that exist between the vehicle (host vehicle) 100a and a position a predetermined distance (distance Do) ahead of the vehicle (host vehicle) 100a in the traveling lane L4 by the distance Do. For example, the traveling_ECU 22 determines the congestion degree J5 of the traveling lane L5 by dividing the number of vehicles 100b that exist between the vehicle (host vehicle) 100a and a position a predetermined distance (distance Do) ahead of the vehicle (host vehicle) 100a in the traveling lane L5 by the distance Do.

[0085] After the vehicle 100c to be monitored has been identified, the driving ECU 22 may acquire the congestion levels J3, J5 (information on the number of vehicles 100b) of the driving lane L1 based on the position information Di of each vehicle 100b traveling in front of the vehicle 100c to be monitored in the driving lanes L3, L5.

[0086] Next, the traveling_ECU 22 determines whether the congestion level J3 is equal to or greater than a threshold value Jth (step S205). If the congestion level J3 is less than the threshold value Jth (step S205; N), the traveling_ECU 22 executes step S201 again. On the other hand, if the congestion level J3 is equal to or greater than the threshold value Jth (step S205; Y), the traveling_ECU 22 determines, as the vehicle 100c to be monitored, the vehicle 100b on the traveling lane L4 that satisfies Si≧Sth and can enter the inter-vehicle space Si (entrance space SSi) on the traveling lane L3 or the traveling lane L5, as shown in FIG. 9 (step S206).

[0087] In addition, the driving_ECU 22 may use the number of vehicles 100b traveling in front of the monitored vehicle 100c in the driving lane L3 instead of the congestion level J3, and may use the number of vehicles 100b traveling in front of the monitored vehicle 100c in the driving lane L5 instead of the congestion level J5.

[0088] In this way, the travel_ECU 22 determines whether the inter-vehicle space Si is an enterable space SSi based on the position information of the vehicle (host vehicle) 100a, the position information Di of each vehicle 100b, and the size information of the inter-vehicle space SSi. If the inter-vehicle space SSi is an enterable space SSi, the travel_ECU 22 executes the following process.

[0089] The travel_ECU 22 predicts a waiting period Tai of the monitored vehicle 100c, or measures an actual measurement period Tbi having a predetermined correlation with the waiting period Tai, based on information acquired while repeatedly executing the above-described processes (e.g., steps S201 to S206) (step S207). The waiting period Tai corresponds to a waiting period predicted to be spent by the monitored vehicle 100c until it starts to change lanes to the entry space SSi on the travel lane L3 or the travel lane L5. If the monitored vehicle 100c continues traveling on the travel lane L4 without changing lanes to the entry space SSi, the waiting period Tai corresponds to a waiting period predicted to be spent until it starts to change lanes to the next entry space SSi on the travel lane L3 or the travel lane L5. The waiting time Tai can be predicted based on, for example, the distance between the monitored vehicle 100c and the accessible space SSi, the speed of the monitored vehicle 100c, and the speed of the vehicle 100b that forms the end of the accessible space SSi.

[0090] The start timing of the waiting time Tai and the actual measurement period Tbi may include various timings, as shown below. For example, suppose that before the determination in step S203, the inter-vehicle space Si was an accessible space SSi into which the monitored vehicle 100c could enter by changing lanes, but the monitored vehicle 100c did not change lanes to the driving lane L3 or the driving lane L5 (hereinafter referred to as "incident A"). In this case, the start timing of the waiting time Tai and the actual measurement period Tbi corresponds to, for example, the timing when incident A occurred. Also, suppose that before the determination in step S203, an incident occurred in which the monitored vehicle 100c encountered traffic congestion in the driving lane L4 (hereinafter referred to as "incident B"). In this case, the start timing of the waiting time Tai and the actual measurement period Tbi may correspond to, for example, the timing when incident B occurred.

[0091] The end timing of the actual measurement period Tbi is, for example, the timing when the determination in step S208 starts. The timing when the determination in step S208 starts is a predetermined period before the monitored vehicle 100c actually starts changing lanes. The end timing of the actual measurement period Tbi is not limited to the timing when the determination in step S208 starts.

[0092] Next, the travel_ECU 22 predicts the possibility that the monitored vehicle 100c will enter the entry space SSi based on the waiting period Tai or the actual measurement period Tbi. Specifically, the travel_ECU 22 determines whether the waiting period Tai or the actual measurement period Tbi is equal to or greater than the threshold value Tth (step S208). As a result, if the waiting period Tai or the actual measurement period Tbi is less than the threshold value Tth (step S208; N), the travel_ECU 22 executes step S201 again. On the other hand, if the waiting period Tai or the actual measurement period Tbi is equal to or greater than the threshold value Tth (step S208; Y), the travel_ECU 22 recognizes the vehicle 100c that satisfies Tai≧Tth or Tbi≧Tth as a vehicle 100d that is at high risk of changing lanes, as shown in FIG. 10 (step S209).

[0093] Next, the traveling_ECU 22 determines whether the entry space SSi is located in the driving lane L3 (step S210). If the entry space SSi is not located in the driving lane L3 (step S210; N), the traveling_ECU 22 executes step S201 again. On the other hand, if the entry space SSi is located in the driving lane L3 (step S210; Y), the traveling_ECU 22 determines whether the entry space SSi is also located in the driving lane L5 (step S211). If the entry space SSi is not located in the driving lane L5 (step S211; N), the traveling control device 10 of the vehicle (host vehicle) 100a executes traveling control that assumes a lane change by the vehicle 100d (step S212).

[0094] On the other hand, if the entry space SSi is also in the driving lane L3 (step S211; Y), the driving_ECU 22 determines whether the congestion level J3 is greater than the congestion level J5 (step S213). As a result, if the congestion level J3 is equal to or less than the congestion level J5 (step S212; N), the driving_ECU 22 executes step S201 again. On the other hand, if the congestion level J3 is greater than the congestion level J5 (step S212; N), the driving control device 10 of the vehicle (host vehicle) 100a executes driving control that assumes a lane change by the vehicle 100d (step S214). In this manner, lane change prediction and driving control are executed in the driving control system 1.

[0095] In this modification, congestion levels J3 and J5 (information on the number of vehicles 100b) of the driving lane L4 are acquired based on the position information Di of each vehicle 100b traveling in the driving lanes L3 and L5. Then, based on the acquired congestion levels J3 and J5, the possibility that the monitored vehicle 100c will enter the entry space SSi of the driving lane L3 is predicted.

[0096] During the waiting period Ti, the driver of the monitored vehicle 100c considers changing lanes to the less crowded lane out of the driving lanes L3 and L5 while looking at the congestion degrees J3 and J5 of the driving lanes L3 and L5 ahead of the vehicle 100c. Therefore, if the congestion degree J3 of the driving lane L3 is smaller than the congestion degree J5 of the driving lane L5, that is, if the driving lane L3 is less crowded than the driving lane L5, the monitored vehicle 100c is more likely to enter the accessible space SSi in the less crowded driving lane L3.

[0097] In this way, in this modification, the possibility that the monitored vehicle 100c will enter the entry space SSi is predicted based on the congestion levels J3 and J5 ahead of the vehicle 100c in the travel lanes L3 and L5 that the driver of the monitored vehicle 100c is observing when attempting to change lanes. This reduces the possibility that unnecessary driving control will occur frequently in preparation for lane changes.

[0098] In this modified example, when the inter-vehicle space Si is an enterable space SSi, the possibility that the monitored vehicle 100c will enter the enterable space SSi is predicted based on the length of the waiting period Ti that the monitored vehicle 100c is predicted to spend before starting to change lanes into the enterable space SSi, or the length of the actual measurement period Tbi that has a predetermined correlation with the waiting period Tai.

[0099] Here, the driver of the monitored vehicle 100c continues to pay attention to the driving lane L3 during the waiting period Ti in order to find the entry space SSi. Therefore, the longer the waiting period Tai, the more irritated the driver of the monitored vehicle 100c becomes, and the less likely he or she is to pay attention to the surrounding traffic conditions. As a result, the driver of the monitored vehicle 100c is more likely to make a recognition error and reflexively change lanes when he or she finds the inter-vehicle space Sb. Therefore, the longer the waiting period Ti, the more likely the monitored vehicle 100c is to change lanes.

[0100] In this way, in this modification, the possibility that the monitored vehicle 100c will enter the entry space SSi is predicted based on the length of the waiting period Tai or the length of the measurement period Tbi, which are highly correlated with the psychological state of the driver of the monitored vehicle 100c that makes the driver more likely to make a recognition error. This makes it possible to reduce the possibility of unnecessary driving control in preparation for lane changes occurring frequently.

[0101] Note that the effects described in this specification are merely examples. The effects of the present disclosure are not limited to the effects described in this specification. The present disclosure may have effects other than the effects described in this specification.

[0102] Furthermore, for example, the present disclosure may be configured as follows: (1) A driving assistance device including a control unit capable of predicting the possibility that a second vehicle will change lanes from a second lane adjacent to a first lane to enter the first lane ahead of a first vehicle traveling on a first lane, wherein the control unit is capable of: acquiring position information of each of a plurality of third vehicles traveling on the first lane including the first vehicle, and size information of an inter-vehicle space ahead of the first vehicle; determining, based on the acquired position information and the acquired size information, whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes; and, if the inter-vehicle space is the enterable space, predicting the possibility that the second vehicle will enter the enterable space based on the length of a waiting period that the second vehicle is expected to spend before starting to change lanes into the enterable space, or the length of an actual measurement period that has a predetermined correlation with the length of the waiting period. (2) The driving assistance device according to (1), wherein, if an incident occurred before the determination that the second vehicle encountered a traffic jam in the second lane even though the inter-vehicle space ahead of the fourth vehicle traveling in the first lane was the entry space, the start timing of the waiting period or the actual measurement period corresponds to the timing when the incident occurred. (3) The driving assistance device according to (1), wherein, if an incident occurred before the determination that the second vehicle encountered a traffic jam in the second lane, the start timing of the waiting period or the actual measurement period corresponds to the timing when the incident occurred.(4) A vehicle including a control unit capable of predicting the possibility of a second vehicle changing lanes to enter ahead of a first vehicle traveling in a first lane from a second lane adjacent to the first lane, wherein the control unit is capable of: acquiring position information of each of a plurality of third vehicles traveling in the first lane, including the first vehicle, and size information of the inter-vehicle space ahead of the first vehicle; determining, based on the acquired position information and the acquired size information, whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes; and, if the inter-vehicle space is the enterable space, predicting the possibility of the second vehicle entering the enterable space based on the length of a waiting period that the second vehicle is expected to spend before starting to change lanes into the enterable space, or the length of an actual measurement period that has a predetermined correlation with the length of the waiting period. (5) A driving assistance method capable of predicting the possibility that a second vehicle will change lanes from a second lane adjacent to a first vehicle traveling in a first lane to enter the first lane in front of the first vehicle, the driving assistance method comprising: acquiring position information of each of a plurality of third vehicles traveling in the first lane, including the first vehicle, and size information of a space between the vehicles in front of the first vehicle; determining, based on the acquired position information and the acquired size information, whether the space between the vehicles is an accessible space into which the second vehicle can enter by changing lanes; and, if the space between the vehicles is the accessible space, predicting the possibility that the second vehicle will enter the accessible space based on the length of a waiting period that the second vehicle is expected to spend before starting to change lanes into the accessible space, or the length of an actual measurement period that has a predetermined correlation with the length of the waiting period.(6) A driving assistance device comprising: a control unit capable of predicting the possibility that a first vehicle traveling in a center lane of three lanes traveling in the same direction will change lanes to enter a right lane or a left lane of the three lanes, wherein the control unit is capable of: acquiring number information of second vehicles traveling ahead of the first vehicle in the right lane and the left lane; and predicting the possibility that the first vehicle will enter the traveling lane based on the acquired number information. (7) The driving assistance device described in (6), wherein the control unit is capable of comparing the number of second vehicles traveling ahead of the first vehicle in the right lane with the number of second vehicles traveling ahead of the first vehicle in the left lane, and predicting that the first vehicle is likely to change lanes to the lane with the smaller number. (8) The control unit is capable of predicting the possibility that the first vehicle will change lanes from the center lane to enter ahead of a third vehicle traveling in the right lane or the left lane, and the control unit is capable of: acquiring position information of each of a plurality of fourth vehicles, including the third vehicle, traveling in the lane in which the third vehicle is traveling, and size information of the inter-vehicle space ahead of the third vehicle; determining, based on the acquired position information and the acquired size information, whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes; and, if the inter-vehicle space is the enterable space, predicting the possibility that the second vehicle will enter the enterable space based on the length of a waiting period that the second vehicle is expected to spend before starting to change lanes into the enterable space, or the length of an actual measurement period that has a predetermined correlation with the length of the waiting period.

[0103] The cruise control device 10 shown in FIG. 1 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 a portion of the various functions of the cruise control device 10 shown in FIG. 1 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 memory can include DRAM and SRAM. Non-volatile memory can include ROM and NVRAM. An ASIC is an integrated circuit (IC) specialized to perform all or a portion of the various functions of the cruise control device 10 shown in FIG. 1. An FPGA is an integrated circuit that is designed to be configurable after manufacture so as to perform all or part of the various functions of the cruise control device 10 shown in FIG.

Claims

1. A driving assistance device comprising a control unit capable of predicting the possibility of a second vehicle changing lanes to enter ahead of a first vehicle traveling on a first lane from a second lane adjacent to the first lane, wherein the control unit is capable of performing the following operations: acquiring position information of each of a plurality of third vehicles traveling on the first lane including the first vehicle, and size information of the inter-vehicle space ahead of the first vehicle; determining whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes based on the acquired position information and the acquired size information; and if the inter-vehicle space is the enterable space, predicting the possibility of the second vehicle entering the enterable space based on the length of a waiting period predicted to be spent by the second vehicle before starting to change lanes into the enterable space, or the length of an actual measured period having a predetermined correlation with the length of the waiting period.

2. The driving assistance device of claim 1, wherein if, before the determination is made, the space ahead of a fourth vehicle traveling in the first lane was the entry space but the second vehicle did not change lanes, the start timing of the waiting period or the actual measurement period corresponds to the timing at which the event occurred.

3. A driving assistance device as described in claim 1, wherein if the second vehicle encounters a traffic jam in the second lane before the determination is made, the start timing of the waiting period or the actual measurement period corresponds to the time when the incident occurs.

4. A vehicle comprising a control unit capable of predicting the possibility of a second vehicle changing lanes to enter ahead of a first vehicle traveling on a first lane from a second lane adjacent to the first lane, wherein the control unit is capable of: acquiring position information of each of a plurality of third vehicles traveling on the first lane including the first vehicle, and size information of the space between the vehicles ahead of the first vehicle; determining whether the space between the vehicles is an enterable space into which the second vehicle can enter by changing lanes based on the acquired position information and the acquired size information; and if the space between the vehicles is the enterable space, predicting the possibility of the second vehicle entering the enterable space based on the length of a waiting period that the second vehicle is predicted to spend before starting to change lanes into the enterable space, or the length of an actual measured period having a predetermined correlation with the length of the waiting period.

5. A driving assistance method capable of predicting the possibility of a second vehicle changing lanes to enter ahead of a first vehicle traveling on a first lane from a second lane adjacent to the first lane, the driving assistance method comprising: acquiring position information of each of a plurality of third vehicles traveling on the first lane including the first vehicle, and size information of the inter-vehicle space ahead of the first vehicle; determining whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes based on the acquired position information and the acquired size information; and if the inter-vehicle space is the enterable space, predicting the possibility of the second vehicle entering the enterable space based on the length of a waiting period predicted to be spent by the second vehicle before starting to change lanes into the enterable space, or the length of an actual measured period having a predetermined correlation with the length of the waiting period.

6. A driving assistance device comprising a control unit capable of predicting the possibility that a first vehicle traveling in a center lane of three lanes all traveling in the same direction will change lanes to enter the right lane or the left lane of the three lanes, wherein the control unit is capable of: acquiring number information of second vehicles traveling ahead of the first vehicle in the right lane and the left lane; and predicting the possibility that the first vehicle will enter the traveling lane based on the acquired number information.

7. The driving assistance device according to claim 6, wherein the control unit is capable of comparing the number of the second vehicles traveling ahead of the first vehicle in the right lane with the number of the second vehicles traveling ahead of the first vehicle in the left lane, and predicting that the first vehicle is highly likely to change lanes to the lane with the smaller number.

8. The driving assistance device according to claim 6, wherein the control unit is capable of predicting the possibility that the first vehicle will change lanes from the center lane to enter ahead of a third vehicle traveling in the right lane or the left lane, and the control unit is capable of: acquiring position information of each of a plurality of fourth vehicles, including the third vehicle, traveling in the lane in which the third vehicle is traveling, and size information of the inter-vehicle space ahead of the third vehicle; determining whether the inter-vehicle space is an enterable space into which the second vehicle can enter by changing lanes, based on the acquired position information and the acquired size information; and, if the inter-vehicle space is the enterable space, predicting the possibility that the second vehicle will enter the enterable space, based on the length of a waiting period that the second vehicle is predicted to spend before starting to change lanes into the enterable space, or the length of an actual measurement period having a predetermined correlation with the length of the waiting period.

Images