Driving assistance device, vehicle, and driving assistance method

Abstract

A driving assistance device according to an embodiment of the present disclosure is provided with a control unit, wherein when a first lane is a congested lane and a second lane adjacent to the first lane is a non-congested lane, if a first vehicle changes lanes to the second lane, the control unit can predict the possibility that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane. This control unit is capable of performing the following three steps: acquiring traffic data about the traveling lanes, the congested lane, the non-congested lane, the first vehicle, and the second vehicle; predicting the time required for the first vehicle to reach a position in the second lane corresponding to a side of the second vehicle after the first vehicle changes lanes, or a time that has a prescribed correlation with the required time, on the basis of the traffic data; and on the basis of the predicted time obtained by the prediction, predicting the possibility that the second vehicle will change lanes from the congested lane to the second lane.

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, various driving assistance devices that perform various controls to assist the driver in driving a vehicle such as an automobile have been proposed and are becoming generally put into practical use. Technologies related to such driving assistance devices are disclosed in, for example, Patent Documents 1 to 5.

[0003] Japanese Patent Application Laid-Open No. 2019-104430 Japanese Patent Application Laid-Open No. 2021-096720 International Publication No. WO2017 / 022447 International Publication No. WO2019 / 138488 Japanese Patent Application Laid-Open No. 2006-085285

[0004] A driving assistance device according to a first aspect of the present disclosure includes a control unit capable of predicting the likelihood that a second vehicle in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane in a road with two or more lanes in each direction, where at least a first lane is a congested lane and at least a second lane adjacent to the first lane is an uncongested lane. The control unit is capable of performing the following (A1), (A2), and (A3): (A1) acquiring traffic data on the driving lanes, the congested lanes, the uncongested lanes, the first vehicle, and the second vehicle; (A2) predicting, based on the traffic data, a time required for the first vehicle to reach a position in the second lane corresponding to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and (A3) predicting the likelihood that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction.

[0005] A vehicle according to a second aspect of the present disclosure includes a control unit capable of predicting the likelihood that a second vehicle in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane in a road with two or more lanes in each direction, where at least a first lane of the road lanes is a congested lane and at least a second lane of the road lanes adjacent to the first lane is an uncongested lane. This control unit is capable of performing the following (B1), (B2), and (B3): (B1) acquiring traffic data on the road lanes, the congested lanes, the uncongested lanes, the first vehicle, and the second vehicle; (B2) predicting, based on the traffic data, the time required for the first vehicle to reach a position in the second lane corresponding to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and (B3) predicting the likelihood that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction.

[0006] A driving assistance method according to a third aspect of the present disclosure is a method capable of predicting the likelihood that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane in a road with two or more lanes in each direction, where at least a first lane of the driving lanes is a congested lane and at least a second lane of the driving lanes adjacent to the first lane is an uncongested lane. This driving assistance method includes the following (C1), (C2), and (C3): (C1) acquiring traffic data on the driving lanes, the congested lanes, the uncongested lanes, the first vehicle, and the second vehicle; (C2) predicting, based on the traffic data, a time required for the first vehicle to reach a position in the second lane corresponding to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and (C3) predicting the likelihood that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction.

[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 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 procedure for predicting the likelihood of a lane change in the cruise control system of FIG. 1. FIG. 3 is a diagram illustrating an example of a processing procedure subsequent to FIG. 2. FIG. 4 is a diagram illustrating an example of traffic conditions in steps S101 to S107 of FIG. 3. FIG. 5 is a diagram illustrating an example of traffic conditions in steps S108 to S111 of FIG. 4. FIG. 6 is a diagram illustrating another example of traffic conditions in steps S108 to S111 of FIG. 4. FIG. 7 is a diagram illustrating a modified example of the procedure for predicting the likelihood of a lane change in the cruise control system of FIG. 1. FIG. 8 is a diagram illustrating an example of traffic conditions in steps S112 to S116 and S109 of FIG. 7. FIG. 9 is a diagram illustrating an example of traffic conditions subsequent to FIG. 8. FIG. 10 is a diagram illustrating a modified example of a processing procedure subsequent to step S108 of FIGS. 3 and 7. FIG. 11 is a diagram illustrating an example of traffic conditions in step S117 of FIG. 10. FIG. 12 is a diagram showing a modified example of the processing procedure following step S108 in FIGS. 3 and 7. FIG. 13 is a diagram showing a modified example of the processing procedure following step S108 in FIG. 3, step S109 in FIG. 7, step S116 in FIG. 7, step S118 in FIG. 10, step S119 in FIG. 12, and step S121 in FIG. 12. FIG. 14 is a diagram showing a hypothetical example of a traffic situation. FIG. 15 is a diagram showing a hypothetical example of a traffic situation following FIG. 14. FIG. 16 is a diagram showing another example of a hypothetical example of a traffic situation. FIG. 17 is a diagram showing a hypothetical example of a traffic situation following FIG. 16.

[0009] 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.

[0010] 1. Background In recent years, various proposals have been made for driving assistance devices that perform various controls to assist the driver in driving operations of vehicles such as automobiles, and these devices are becoming generally practical. For example, in a conventional driving assistance device, when a congested lane is present ahead of a host vehicle, it is conceivable to predict the presence of a vehicle that attempts to change lanes from the congested lane to an uncongested lane, and to notify the driver of the host vehicle of the presence of such a vehicle.

[0011] FIG. 14 illustrates a hypothetical example of a traffic situation. A plurality of vehicles 100, including a vehicle (host vehicle) 100x, are traveling on a road with three lanes on each side. This three-lane road is composed of a driving lane L, the three lanes on which the vehicle 100x is traveling, and an oncoming lane (not shown) that runs parallel to the driving lane L via a center line. The driving lane L has three lanes (a first lane L1, a second lane L2, and a third lane L3). The first lane L1 is the lane closest to the center line. The second lane L2 is a so-called passing lane and is located between the first lane L1 and the third lane L3. The third lane L3 is also a so-called passing lane and is located farthest from the center line.

[0012] A vehicle 100x is traveling in the second lane L2, and a number of vehicles 100 are stopped or moving slowly ahead of the vehicle 100x. In other words, the second lane L2 has a section (a congested lane) in front of the vehicle 100x where a number of vehicles 100 are stopped or moving slowly. In this specification, "driving slowly" refers to traveling at a speed of less than 10 km / h, for example. A number of vehicles 100 are also stopped or moving slowly ahead of the vehicle 100x in the first lane L1. In other words, the first lane L1 also has a congested lane ahead of the vehicle 100x. In the third lane L3, one or more vehicles 100 are traveling ahead of the vehicle 100x. In other words, the third lane L3 has an uncongested lane ahead of the vehicle 100x. In this specification, "driving" means that the vehicle 100 is not stopped or slowing down, but is traveling at a speed faster than slowing down (for example, a speed of 10 km / h or more).

[0013] In the second lane L2, a vehicle 100y is present ahead of the last vehicle (last vehicle in the traffic jam) 100z1 in the congested section (congested lane). The vehicle 100y is caught in the traffic jam in the second lane L2. At this time, the driver of the vehicle 100y notices that the third lane L3 adjacent to the second lane L2 is open and intends to change lanes of the vehicle 100y from the second lane L2 to the third lane L3. Meanwhile, a vehicle 100x is approaching the vehicle 100z1 from the rear of the traffic jam in which the vehicle 100y is caught. The driver of the vehicle 100x notices that traffic jams have occurred ahead of the vehicle 100x in the first lane L1 and the second lane L2 and intends to change lanes of the vehicle 100x from the second lane L2 to the third lane L3.

[0014] Although the driver of vehicle 100y checks the rear of vehicle 100y in the third lane L3 using the side mirror and visually, vehicle 100x has not yet started moving into the third lane L3 at this time, and vehicle 100y is therefore unable to see vehicle 100x. Therefore, the driver of vehicle 100y is unaware of the presence of vehicle 100x and begins to move vehicle 100y from the second lane L2 to the third lane L3 while avoiding vehicle 100z2 (forward vehicle) located in front of vehicle 100y. Meanwhile, the driver of vehicle 100x happens to start moving vehicle 100x from the second lane L2 to the third lane L3 immediately after the driver of vehicle 100y checks the rear of vehicle 100y in the third lane L3 using the side mirror and visually. The driver of vehicle 100x notices that vehicle 100y has started to change lanes from second lane L2 to third lane L3 at the same time that vehicle 100x has completed its lane change from second lane L2 to third lane L3. However, at this time, the driver of vehicle 100x is unable to brake to avoid vehicle 100y, and as a result, for example, as shown in FIG. 15 , vehicle 100y and vehicle 100x collide with each other in third lane L3.

[0015] FIG. 16 illustrates another hypothetical traffic situation. A plurality of vehicles 100, including a vehicle 100x, are traveling on a four-lane road. This four-lane road is composed of a four-lane driving lane L on which the vehicle 100x is traveling and an oncoming lane (not shown) that runs parallel to the driving lane L via a center line. The driving lane L has four lanes (a first lane L1, a second lane L2, a third lane L3, and a fourth lane L4). The first lane L1 is the lane closest to the center line. The second lane L2 is a so-called passing lane and is located between the first lane L1 and the third lane L3. The third lane L3 is also a so-called passing lane and is located between the second lane L2 and the fourth lane L4. The fourth lane L4 is also a so-called passing lane and is located farthest from the center line.

[0016] Vehicle 100x is traveling in the fourth lane L4, and a large number of vehicles 100 are stopped or moving slowly in front of vehicle 100x. In other words, the fourth lane L4 has a congested lane in front of vehicle 100x. A large number of vehicles 100 are also stopped or moving slowly in front of vehicle 100x in the first lane L1. In other words, the first lane L1 also has a congested lane in front of vehicle 100x. A large number of vehicles 100 are also stopped or moving slowly in front of vehicle 100x in the second lane L2. In other words, the second lane L2 also has a congested lane in front of vehicle 100x. One or more vehicles 100 are traveling in front of vehicle 100x in the third lane L3. In other words, the third lane L3 has an uncongested lane in front of vehicle 100x.

[0017] In the second lane L2, a vehicle 100y is present ahead of the last vehicle (last vehicle in the traffic jam) 100z1 in the congested section (congested lane). The vehicle 100y is caught in the traffic jam in the second lane L2. At this time, the driver of the vehicle 100y notices that the third lane L3 adjacent to the second lane L2 is open and intends to change lanes of the vehicle 100y from the second lane L2 to the third lane L3. Meanwhile, from behind the traffic jam in which the vehicle 100y is caught, a vehicle 100x is approaching the last vehicle (last vehicle in the traffic jam) 100z3 in the congested section in the fourth lane L4 (the last vehicle in the traffic jam). The driver of vehicle 100x notices that there is congestion ahead of vehicle 100x in the first lane L1, the second lane L2, and the fourth lane L4, and intends to change lanes of vehicle 100x from the fourth lane L4 to the third lane L3.

[0018] Although the driver of vehicle 100y checks the rear of vehicle 100y in the third lane L3 using the side mirror and visually, vehicle 100x has not yet started moving into the third lane L3 at this time, and vehicle 100y is therefore unable to see vehicle 100x. Therefore, the driver of vehicle 100y is unaware of the presence of vehicle 100x and begins to move vehicle 100y from the second lane L2 to the third lane L3 while avoiding vehicle 100z2 (forward vehicle) located in front of vehicle 100y. Meanwhile, the driver of vehicle 100x happens to start moving vehicle 100x from the fourth lane L4 to the third lane L3 immediately after the driver of vehicle 100y checks the rear of vehicle 100y in the third lane L3 using the side mirror and visually. The driver of vehicle 100x notices that vehicle 100y has started to change lanes from fourth lane L4 to third lane L3 at the same time that vehicle 100x has completed its lane change from fourth lane L4 to third lane L3. However, at this time, the driver of vehicle 100x is unable to brake to avoid vehicle 100y, and as a result, for example, as shown in FIG. 17 , vehicle 100y and vehicle 100x collide with each other in third lane L3.

[0019] Such collisions occurring when passing through the side of a congested lane occur due to the driver of vehicle 100y failing to notice vehicle 100x. Therefore, the present inventors conceived of predicting the possibility that vehicle 100y will change lanes from a congested lane to an uncongested lane in a specific traffic situation where the driver of vehicle 100y is likely to fail to notice vehicle 100x. Specifically, the present inventors conceived of determining whether the traffic situation around vehicle 100x is the above-mentioned specific traffic situation based on a prediction (predicted time) of the time required for vehicle 100x to reach a position in the new lane corresponding to the side of vehicle 100y after changing lanes. The shorter this predicted time, the more likely the driver of vehicle 100y is to fail to notice vehicle 100x. A traffic situation where this predicted time is equal to or less than a predetermined threshold can be considered the above-mentioned specific traffic situation. Below, a cruise control system using the above-mentioned predicted time will be described in detail.

[0020] 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.

[0021] 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.

[0022] 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.

[0023] Static information that makes up road information includes information that needs to be updated within one month, such as roads, road structures, lane information, road surface information, and permanent traffic regulations. "Roads" include, for example, road locations and shapes, intersections, and road attributes (e.g., national roads, prefectural roads, city roads, private roads, priority roads, non-priority roads, general roads, and expressways). "Road structures" include, for example, traffic signs, traffic lights, convex mirrors, and pedestrian bridges.

[0024] The quasi-static information that constitutes the road information is made up of information that needs to be updated every hour, such as traffic regulation information due to road construction or events, wide-area weather information, and congestion forecasts.

[0025] The semi-dynamic information that constitutes traffic information is composed of information that requires updating within one minute, such as the actual traffic congestion situation at the time of observation, driving restrictions, temporary driving obstructions such as fallen objects and obstacles, actual accident conditions, and narrow-area weather information.

[0026] The dynamic information that makes up the traffic information is made up of information that needs to be updated every second, such as information sent and exchanged between mobile bodies, information on currently displayed traffic signals, information on pedestrians and bicycles at intersections, information on vehicles traveling on roads, etc. 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 transmitted to each vehicle as appropriate via the transceiver 202.

[0027] 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 "cruise_ECU") 21, an engine control unit (hereinafter referred to as "E / G_ECU") 22, a power steering control unit (hereinafter referred to as "PS_ECU") 23, and a brake control unit (hereinafter referred to as "BK_ECU") 24. These control units 21 to 24 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).

[0028] The travel_ECU 21 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 there is a traffic jam ahead of the vehicle (host vehicle) and the vehicle changes lanes to avoid the traffic jam, the travel_ECU 21 can control the vehicle to avoid a collision with a vehicle that jumps out in front of the vehicle (host vehicle) due to the lane change. Detailed processing content in the driving control mode will be described later.

[0029] A throttle actuator 25 is connected to the output side of the E / G_ECU 22. This throttle actuator 25 opens and closes a throttle valve of an electronically controlled throttle provided in a throttle body of the engine. The E / G_ECU 22 controls the operation of the throttle actuator 25 by outputting a drive signal to the throttle actuator 25. The throttle actuator 25 opens and closes the throttle valve based on the drive signal from the E / G_ECU 22 to adjust the intake air flow rate, thereby generating a desired engine output.

[0030] An electric power steering motor 26 is connected to the output side of the PS_ECU 23. This electric power steering motor 26 applies steering torque to the steering mechanism by the rotational force of the motor. The PS_ECU 23 controls the operation of the electric power steering motor 26 by outputting a drive signal to the electric power steering motor 26. During autonomous driving, the electric power steering motor 26 performs 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.), based on the drive signal from the PS_ECU 23.

[0031] A brake actuator 27 is connected to the output side of the BK_ECU 24. This brake actuator 27 adjusts the brake hydraulic pressure supplied to the brake wheel cylinders provided on each wheel. The BK_ECU 24 controls the operation of the brake actuator 27 by outputting a drive signal to the brake actuator 27. Based on the drive signal from the BK_ECU 24, the brake actuator 27 generates a braking force on each wheel using the brake wheel cylinders, forcibly decelerating the wheel.

[0032] 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.

[0033] 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 are capable of capturing stereo images of the area in front of the vehicle from different viewpoints.

[0034] The IPU 11c is capable of generating a distance image calculated from the amount of deviation in the positions of corresponding objects 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.

[0035] The driving environment detection unit 11d can, for example, determine 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 can also, for example, determine the road curvature [1 / m] of the markings that divide the left and right sides of the road (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 can also, for example, perform predetermined pattern matching on the distance image to detect lanes and three-dimensional objects such as structures that exist around the vehicle.

[0036] 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, pedestrians, and various buildings. The driving environment detection unit 11d is capable of outputting information about the detected three-dimensional objects to the driving_ECU 21, for example.

[0037] 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 is capable of detecting the longitudinal acceleration of the vehicle. The vehicle speed sensor 15 is capable of detecting the vehicle's speed. The gyro sensor 16 is capable of detecting the vehicle's angular velocity or angular acceleration. The GNSS receiver 17 is capable of receiving 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.

[0038] 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.

[0039] 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.

[0040] The vehicle position estimation unit 13b is capable of acquiring 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 is also capable of estimating 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 is capable of acquiring 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.

[0041] 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 can switch 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 estimate the vehicle's position on a road map.

[0042] As described above, the vehicle position estimation unit 13b estimates the position of the vehicle (host vehicle position) on a road map based on the positioning signal received by the GNSS receiver 17 or information detected by the gyro sensor 16, etc., and is then able to determine the road type, etc. of the road on which the vehicle (host vehicle) is traveling based on the estimated host vehicle position on the road map.

[0043] The driving environment recognition unit 13c is capable of updating the road map information stored in the high-precision road map database 19 to the latest state by 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 for static information but also for 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 real time.

[0044] 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 is capable of updating 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.

[0045] 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 is capable of outputting, 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 21.

[0046] Next, the travel_ECU 22 will be described in detail.

[0047] Figures 2 and 3 show an example of a procedure for predicting the possibility of a lane change in the cruise control system 1. Figure 4 shows an example of traffic conditions in steps S101 to S107 in Figure 2. Figures 5 and 6 show an example of traffic conditions in steps S108 to S111 in Figure 3.

[0048] In FIG. 4 , vehicles 100 including vehicle (host vehicle) 100x are traveling on a road with three lanes on each side. Vehicle 100x corresponds to a specific example of a “first vehicle” according to an embodiment of the present disclosure. This three-lane road is composed of a three-lane driving lane L on which vehicles 100 including vehicle 100x are traveling, and an opposite lane (not shown) that runs along driving lane L with a center line interposed therebetween. Driving lane L has three lanes (a first lane L1, a second lane L2, and a third lane L3). The first lane L1 is the lane closest to the center line. The second lane L2 is a so-called passing lane and is located between the first lane L1 and the third lane L3. The third lane L3 is also a so-called passing lane and is located farthest from the center line.

[0049] A vehicle 100x is traveling in the second lane L2, and a number of vehicles 100 are stopped or moving slowly ahead of the vehicle 100x. In other words, the second lane L2 has a congested lane ahead of the vehicle 100x. A number of vehicles 100 are also stopped or moving slowly ahead of the vehicle 100x in the first lane L1. In other words, the first lane L1 also has a congested lane ahead of the vehicle 100x. One or more vehicles 100 are traveling in the third lane L3 ahead of the vehicle 100x. In other words, the third lane L3 has an uncongested lane ahead of the vehicle 100x.

[0050] In the second lane L2, vehicles 100y1 and 100y2 are present ahead of vehicle 100z1, which is at the rear of the congested section (last vehicle in the traffic jam). Vehicles 100y1 and 100y2 correspond to a specific example of a "second vehicle" according to an embodiment of the present disclosure. Vehicles 100y1 and 100y2 are caught in the traffic jam in the second lane L2. At this time, the drivers of vehicles 100y1 and 100y2 notice that the third lane L3 adjacent to the second lane L2 is empty and intend to change lanes of vehicles 100y1 and 100y2 from the second lane L2 to the third lane L3. Meanwhile, vehicle 100x is approaching vehicle 100z1 from the rear of the traffic jam in which vehicles 100y1 and 100y2 are caught. The driver of vehicle 100x notices that there is congestion ahead of vehicle 100x in the first lane L1 and the second lane L2, and intends to change lanes of vehicle 100x from the second lane L2 to the third lane L3.

[0051] Although the driver of vehicle 100y checks the rear of vehicle 100y in the third lane L3 using the side mirror and visually, vehicle 100x has not yet started moving into the third lane L3 at this time, and vehicle 100y is therefore unable to see vehicle 100x. Therefore, the driver of vehicle 100y is unaware of the presence of vehicle 100x and begins to move vehicle 100y from the second lane L2 to the third lane L3 while avoiding vehicle 100z2 (forward vehicle) located in front of vehicle 100y. Meanwhile, the driver of vehicle 100x happens to start moving vehicle 100x from the second lane L2 to the third lane L3 immediately after the driver of vehicle 100y checks the rear of vehicle 100y in the third lane L3 using the side mirror and visually. The driver of vehicle 100x notices that vehicle 100y has started to change lanes from second lane L2 to third lane L3 at the same time that vehicle 100x has completed its lane change from second lane L2 to third lane L3. However, at this time, the driver of vehicle 100x is unable to brake to avoid vehicle 100y, and as a result, there is a high possibility that vehicles 100y and 100x will collide with each other in third lane L3.

[0052] Therefore, the traveling_ECU 21 is capable of performing calculations that take such events into consideration. Specifically, before the vehicle 100x starts changing lanes, the traveling_ECU 21 is capable of determining whether the traffic conditions around the vehicle 100x are in the specific traffic conditions described above. After determining that the traffic conditions around the vehicle 100x are in the "specific traffic condition TS," the traveling_ECU 21 is capable of identifying one or more vehicles that are physically capable of changing lanes from a congested lane to an uncongested lane as "monitored vehicles MC." When the vehicle 100x changes lanes, the traveling_ECU 21 is capable of calculating a "predicted time tp" for each monitored vehicle MC, and calculating a possibility TC that the monitored vehicle MC will change lanes from a congested lane to an uncongested lane, for each monitored vehicle MC, based on the calculated predicted time tp. The driving_ECU 21 is capable of recognizing a monitored vehicle MC whose lane change possibility TC is equal to or greater than a predetermined threshold TCth as a dangerous vehicle and notifying the driver of vehicle 100x of the presence of the dangerous vehicle.

[0053] (Specific Traffic Condition TS) Specifically, specific traffic condition TS refers to a traffic condition that satisfies all of the following conditions: - There are two or more lanes of travel in each direction ahead of vehicle 100x - There is a congested lane ahead of vehicle 100x - There is an uncongested lane ahead of vehicle 100x - There is an uncongested lane among the lanes adjacent to the lane in which vehicle 100x is traveling - There is a congested lane among the lanes adjacent to the uncongested lane - Vehicle 100x can change lanes into the uncongested lane

[0054] For example, in FIG. 4 , there are two or more lanes of traffic ahead of vehicle 100x, including congested lanes Lj1 and Lj2 and an uncongested lane Lu1 ahead of vehicle 100x, and an uncongested lane Lu1 in a third lane L3 adjacent to the second lane L2 in which vehicle 100x is traveling. For example, in FIG. 4 , if a vehicle traveling behind vehicle 100x in the third lane L3 exists, the inter-vehicle distance between that vehicle and vehicle 100x is equal to or greater than a predetermined threshold (e.g., 30 m). At this time, vehicle 100x is able to change lanes into the third lane L3. Therefore, the traffic situation shown in FIG. 4 corresponds to a specific traffic situation TS.

[0055] (Monitored vehicle MC) A monitored vehicle MC refers to a vehicle that is physically capable of changing lanes from a congested lane to a non-congested lane (hereinafter referred to as a "specific non-congested lane") that is located among the lanes adjacent to the lane in which vehicle 100x is traveling in a specific traffic situation TS.

[0056] For example, in FIG. 4, two vehicles 100y1 and 100y2 located in the congested lane Lj2 of the second lane L2 are vehicles that can change lanes to the uncongested lane Lu1 in the third lane L3. Therefore, the vehicles 100y1 and 100y2 correspond to the monitored vehicles MC. In practice, it is necessary to identify a vehicle that may collide with the vehicle 100x by changing lanes as the monitored vehicle MC. Therefore, a vehicle that is physically capable of changing lanes into the space between the vehicle 100y3, which is closest to the vehicle 100x, and the vehicle 100x in the uncongested lane Lu1 corresponds to the monitored vehicle MC. For example, in FIG. 4, the vehicles 100y1 and 100y2 are vehicles that can change lanes into the above-mentioned space. Therefore, the vehicles 100y1 and 100y2 correspond to the monitored vehicles MC.

[0057] In addition, vehicles that are in a position where the presence of vehicle 100x can be recognized even before changing lanes may be excluded from the monitored vehicles MC. For example, in Fig. 4, the driver of vehicle 100z1 located at the rear of congested lane Lj2 in second lane L2 recognizes that vehicle 100x is approaching from behind, and under such circumstances, the driver is unlikely to attempt a lane change from second lane L2 to third lane L3. Therefore, vehicle 100z1 may be excluded from the monitored vehicles MC.

[0058] (Predicted time tp) The predicted time tp is calculated for each monitored vehicle MC. The predicted time tp is the time required for the vehicle 100x to reach a position on the lane after the lane change that corresponds to the side of the monitored vehicle MC. For example, the predicted time tp is the time required for the vehicle 100x to reach a position on the lane after the lane change that corresponds to the side of the monitored vehicle MC after the lane change that corresponds to the side of the monitored vehicle MC after the lane change.

[0059] The predicted time tp1 for the vehicle 100y1 is calculated, for example, by D1 / v1 as shown in FIG. 5. The predicted time tp2 for the vehicle 100y2 is calculated, for example, by D2 / v1 as shown in FIG. 5. D1 is the distance between the front end (e.g., front bumper) of the vehicle 100x and the rear end (e.g., rear bumper) of the vehicle 100y1 at time t1 when the vehicle 100x completes the lane change. D2 is the distance between the front end (e.g., front bumper) of the vehicle 100x and the rear end (e.g., rear bumper) of the vehicle 100y2 at time t1. v1 is the speed of the vehicle 100x at time t1.

[0060] The predicted time tp may be, for example, the time required for the vehicle 100x to reach a position in the lane after the lane change that corresponds to the side of the monitored vehicle MC from the time the vehicle 100x starts changing lanes. In this case, the predicted time tp3 for the vehicle 100y1 is calculated, for example, by D3 / v2 as shown in FIG. 6 . The predicted time tp4 for the vehicle 100y2 is calculated, for example, by D4 / v2 as shown in FIG. 6 . D3 is the distance between the front end (e.g., front bumper) of the vehicle 100x and the rear end (e.g., rear bumper) of the vehicle 100y1 at time t2 when the vehicle 100x starts changing lanes. D2 is the distance between the front end (e.g., front bumper) of the vehicle 100x and the rear end (e.g., rear bumper) of the vehicle 100y2 at time t2. v2 is the speed of the vehicle 100x at time t2.

[0061] The traveling_ECU 21 can determine the time when the lane change is completed, for example, by detecting the end of blinking of the turn signals of the vehicle 100x via an in-vehicle communication line such as a CAN. The traveling_ECU 21 can also detect the time when the lane change is completed, for example, as follows. For example, the traveling_ECU 21 first detects the traveling lane of the vehicle 100x based on the stereo image obtained by the traveling-environment recognition unit 11, and extracts the number or ID, etc. assigned to the detected traveling lane from road map information obtained via external communication. Then, the traveling_ECU 21 can determine the time when the number or ID, etc. assigned to the traveling lane of the vehicle 100x changes, as the time when the lane change is completed.

[0062] The traveling_ECU 21 can also detect the time (time) when the lane change is completed, for example, as follows: For example, the traveling_ECU 21 first detects the lane in which the vehicle 100x is traveling based on the position information of the vehicle 100x obtained by the GNSS receiver 17 and road map information acquired via external communication. Then, the traveling_ECU 21 can determine the time (time) when it detects that the vehicle 100x has moved to an adjacent lane as the time (time) when the lane change is completed.

[0063] The traveling_ECU 21 can determine the time (time) when the lane change started as, for example, the time (time) when the start of blinking of the turn signal of the vehicle 100x is detected via an in-vehicle communication line such as a CAN. The traveling_ECU 21 can also determine the time (time) when the lane change started as the time (time) when one of the front tires of the vehicle 100x crosses the boundary line between the lane in which the vehicle 100x is traveling (the lane before the lane change) and the lane after the lane change.

[0064] The traveling_ECU 21 is capable of determining that the front tires of the vehicle 100x have crossed the boundary line. For example, the traveling_ECU 21 first detects lane boundaries included in the stereo images obtained by the traveling-environment recognition unit 11 and estimates the position of the detected boundary line. The traveling_ECU 21 then virtually extends the boundary line whose position has been estimated to an area blocked by the hood of the vehicle 100x or the like, and when the position of the extended boundary line overlaps with the position of the front tires that has been registered in advance, the traveling_ECU 21 is capable of determining that the front tires of the vehicle 100x have crossed the boundary line.

[0065] The traveling_ECU 21 may be capable of determining that the front tires of the vehicle 100x have crossed the boundary line, for example, as follows: For example, the traveling_ECU 21 first derives the position of the boundary line between the lane in which the vehicle 100x is traveling (the lane before the lane change) and the lane after the lane change, based on the position information of the vehicle 100x obtained by the GNSS receiver 17 and road map information acquired via external communication. Then, the traveling_ECU 21 is capable of determining that the front tires of the vehicle 100x have crossed the boundary line when the derived position of the boundary line overlaps with the position of the front tires derived from the position information of the vehicle 100x.

[0066] (Lane Change Probability TC) The lane change possibility TC is calculated for each monitored vehicle MC. The lane change possibility TC is calculated based on the predicted time tp. The lane change possibility TC1 of the vehicle 100y1 is calculated, for example, as shown in FIG. 5, by α1×exp(-β1×Δt+tp1). The lane change possibility TC2 of the vehicle 100y2 is calculated, for example, as shown in FIG. 5, by α1×exp(-β1×Δt+tp2). α1 and β1 are constants. Δt is the time from time t1 to time t2, that is, the time required for the vehicle 100x to change lanes.

[0067] The possibility TC1 that the vehicle 100y1 will change lanes may be calculated, for example, as shown in Figure 6, by α2 × exp(-β2 × tp3). The possibility TC2 that the vehicle 100y2 will change lanes is calculated, for example, as shown in Figure 6, by α2 × exp(-β2 × tp4). α2 and β2 are constants.

[0068] (Driving Assistance Procedure) Next, a driving assistance procedure in the cruise control system 1 will be described with reference to Figures 2, 3, 4, 5, and 6. First, a stereo camera provided on the vehicle 100x captures images of the area ahead of the vehicle 100x and outputs the resulting stereo images 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 the driving lane L, the first lane L1, the second lane L2, the second lane L3, and each vehicle 100 on the driving lane L.

[0069] Next, the driving environment recognition unit 13c uses road map information acquired via external communication to detect the driving lane L, the first lane L1, the second lane L2, the second lane L3, and each vehicle 100 on the driving lane L. Here, it is assumed that the road map information acquired via external communication includes information on each vehicle 100 on the driving lane L. In this case, the driving environment recognition unit 13c can detect information on each vehicle 100 on the driving lane L by using the road map information acquired via external communication.

[0070] The vehicle position estimation unit 13b acquires the position coordinates of the vehicle 100x based on the positioning signal received by the GNSS receiver 17. The vehicle position estimation unit 13b further acquires the vehicle speed (speed of the vehicle 100x) detected by the vehicle speed sensor 15.

[0071] Next, the travel_ECU 21 acquires road information Da and vehicle information Db based on various information obtained from the travel environment detection unit 11d, the vehicle position estimation unit 13b, and the travel environment recognition unit 13c (step S101). The road information Da and the vehicle information Db correspond to a specific example of "traffic data" according to an embodiment of the present disclosure. Here, the road information Da includes information about the travel lane L, the first lane L1, the second lane L2, and the third lane L3 detected by the travel environment detection unit 11d or the travel environment recognition unit 13c. The vehicle information Db includes information about the speed (vehicle speed) of the vehicle 100x acquired from the vehicle position estimation unit 13b and information about each vehicle 100 on the travel lane L acquired from the travel environment detection unit 11d or the travel environment recognition unit 13c.

[0072] Next, the traveling_ECU 21 determines whether there are two or more driving lanes in each direction ahead of the vehicle 100x (step S102). If the road information Da includes information on the driving lane L (step S102; Y), the traveling_ECU 21 determines whether there are any congestion lanes ahead of the vehicle 100x (step S103). If the vehicle information Db includes position information and speed information of multiple vehicles 100 ahead of the vehicle 100x, the traveling_ECU 21 determines whether there are any congestion lanes ahead of the vehicle 100x in the first lane L1, the second lane L2, and the third lane L3 based on the position information and speed information of the multiple vehicles 100 included in the vehicle information Db. As a result, the traveling_ECU 21 determines that there are congestion lanes ahead of the vehicle 100x, for example, in the first lane L1 and the second lane L2 (step S103; Y).

[0073] If it is determined that a congested lane exists, the traveling_ECU 21 determines whether or not a non-congested lane exists ahead of the vehicle 100x (step S104). If the vehicle information Db includes position information and speed information of multiple vehicles 100 ahead of the vehicle 100x, the traveling_ECU 21 determines whether or not a non-congested lane exists ahead of the vehicle 100x in the first lane L1, the second lane L2, or the third lane L3 based on the position information and speed information of the multiple vehicles 100 included in the vehicle information Db. As a result, the traveling_ECU 21 determines that, for example, a non-congested lane exists ahead of the vehicle 100x in the third lane L3 (step S104; Y).

[0074] If it is determined that a non-congested lane exists, the traveling_ECU 21 identifies the lane in which the vehicle 100x is traveling (step S105). The traveling_ECU 21 identifies the lane in which the vehicle 100x is traveling based on the position coordinates of the vehicle 100x acquired by the vehicle position estimation unit 13b and the road information Da. For example, the traveling_ECU 21 identifies the lane in which the vehicle 100x is traveling as the second lane L2.

[0075] When the lane in which the vehicle 100x is traveling has been identified, the traveling_ECU 21 determines whether the traffic conditions around the vehicle 100x are specific traffic conditions TS (step S106). Specifically, the traveling_ECU 21 first determines whether an uncongested lane exists among the lanes adjacent to the lane in which the vehicle 100x is traveling, and whether a congested lane exists among the lanes adjacent to the uncongested lane (condition A). For example, the traveling_ECU 21 determines that the lane (third lane L3) adjacent to the lane in which the vehicle 100x is traveling (second lane L2) is an uncongested lane (hereinafter referred to as a "specific uncongested lane"), and that the lane (second lane L2) adjacent to the specific uncongested lane (third lane L3) is a congested lane (hereinafter referred to as a "specific congested lane").

[0076] The traveling_ECU 21 further determines whether the vehicle 100x can change lanes to a specific non-congested lane (condition B). Specifically, if there is a vehicle 100 traveling behind the vehicle 100x in the specific non-congested lane, the traveling_ECU 21 determines whether the inter-vehicle distance between the vehicle 100 and the vehicle 100x is equal to or greater than a predetermined threshold (e.g., 30 m). If the inter-vehicle distance is equal to or greater than the predetermined threshold, the traveling_ECU 21 determines that the vehicle 100x can change lanes to a specific non-congested lane. In this way, if the traffic conditions around the vehicle 100x satisfy the above steps S102 to S104 and both conditions A and B, the traveling_ECU 21 determines that the traffic conditions around the vehicle 100x are the specific traffic conditions TS (step S106; Y).

[0077] For example, the traveling_ECU 21 recognizes, as the monitored vehicles MC, the vehicles 100 that satisfy the above-described conditions among the multiple vehicles 100 included in the congested lane Lj2 in the specific traffic situation TS (step S107). For example, as shown in FIG. 4, the traveling_ECU 21 recognizes, as the monitored vehicles MC, multiple vehicles (e.g., two vehicles 100y1 and 100y2) located in front of the last vehicle 100z1 in the congested lane Lj2. The traveling_ECU 21 calculates the predicted time tp for each vehicle (e.g., two vehicles 100y1 and 100y2) recognized as the monitored vehicles MC (step S108).

[0078] The travel_ECU 21 calculates the lane change probability TC of each of the vehicles 100y1 and 100y2 based on the predicted time tp (step S109). The travel_ECU 21 determines whether the lane change probability TC of each of the vehicles 100y1 and 100y2 is equal to or greater than a predetermined threshold TCth (step S110). If the travel_ECU 21 determines that there is a vehicle 100 whose lane change probability TC is equal to or greater than the predetermined threshold TCth (step S110; Y), the travel_ECU 21 notifies the driver of the vehicle (host vehicle) 100x that the vehicle 100 may jump out in front of the vehicle (host vehicle) 100x due to a lane change (step S111). The travel_ECU 21 generates, for example, a sound signal (control signal) for outputting a predetermined sound and outputs the sound to a speaker mounted on the vehicle (host vehicle) 100x. When a sound signal is input from the travel_ECU 21, the speaker outputs a sound corresponding to the input sound signal.

[0079] The travel_ECU 21 executes step S101 if any of the following conditions is met in each of the above steps: - The road information Da does not include information on the travel lane L (step S102; N); - A congested lane does not exist ahead of the vehicle 100x (step S103; N); - A non-congested lane does not exist ahead of the vehicle 100x (step S104; N); - The traffic situation ahead of the vehicle 100x is not a specific traffic situation (step S106; N); - The possibility TC of a lane change is less than a predetermined threshold TCth (step S110; N).

[0080] [Effects] Next, effects of the cruise control system 1 according to one embodiment of the present disclosure will be described.

[0081] In this embodiment, the predicted time tp is calculated based on the acquired road information Da and vehicle information Db, and the possibility TC of each vehicle 100y1, 100y2 changing lanes is predicted based on the calculated predicted time tp. This allows the driver of vehicle 100x to be aware of the presence of vehicle 100 that is about to change lanes from the congested lane when passing by the side of the congested lane at an early stage, thereby avoiding a collision accident that may occur when passing by the side of the congested lane.

[0082] Furthermore, when the possibility of a collision is simply predicted based on road information Da and vehicle information Db, it is easy to determine that there is a high possibility that vehicle 100 will jump out of the congested lane by changing lanes, even in a situation where the driver of vehicle 100 in the congested lane is unlikely to overlook vehicle 100x. On the other hand, in this embodiment, the lane change possibility TC of each vehicle 100y1, 100y2 is predicted based on prediction time tp, so that it is possible to determine that there is a low possibility that vehicle 100 will jump out of the congested lane by changing lanes, when the driver of vehicle 100 in the congested lane is unlikely to overlook vehicle 100x. Therefore, in this embodiment, it is possible to avoid unnecessary notifications to the driver of vehicle 100x.

[0083] In this embodiment, if the time required for the vehicle 100x to reach a position on the lane after the lane change that corresponds to the side of the monitored vehicle MC after the lane change is the predicted time tp, the driver of the vehicle 100x can be notified early on of the presence of the vehicle 100 that is about to jump out of the congested lane by changing lanes when passing by the side of the congested lane, thereby avoiding a collision accident that occurs when passing by the side of the congested lane.

[0084] In this embodiment, if the time required for the vehicle 100x to reach a position on the lane after the lane change that corresponds to the side of the monitored vehicle MC from the time the vehicle 100x starts changing lanes is the predicted time tp, the driver of the vehicle 100x can be notified earlier of the presence of the vehicle 100 that is about to jump out of the congested lane by changing lanes when passing by the side of the congested lane, thereby avoiding a collision accident that occurs when passing by the side of the congested lane.

[0085] In this embodiment, a sound signal (control signal) is generated to notify the driver of the vehicle (host vehicle) 100x that there is a possibility that the vehicle 100 may jump out in front of the vehicle (host vehicle) 100x, and the sound signal (control signal) is output to a speaker mounted on the vehicle (host vehicle) 100x. This allows the driver of the vehicle 100x to be notified early on of the presence of the vehicle 100 that may jump out by changing lanes from the congested lane when passing by the side of the congested lane. Therefore, it is possible to avoid a collision accident that occurs when passing by the side of the congested lane.

[0086] 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.

[0087] [Variant 3-1] In the above embodiment, the driving_ECU 21 may be configured to determine the possibility TC of the monitored vehicle MC changing lanes based on the steering angle θ of the front wheels of the monitored vehicle MC and the inter-vehicle distance D between the monitored vehicle MC and the vehicle 100 in front of the monitored vehicle MC.

[0088] Fig. 7 shows a modified example of the procedure for predicting the possibility of a lane change in the cruise control system 1. Fig. 8 shows an example of traffic conditions in steps S112 to S116 and S109 in Fig. 7. Fig. 9 shows an example of traffic conditions following Fig. 8. Fig. 10 shows an example of traffic conditions in steps S112 to S116 and S109 in Fig. 7. Fig. 11 shows an example of traffic conditions following Fig. 10.

[0089] For example, as shown in Fig. 8, assume that a vehicle 100y2 is present ahead of a vehicle 100y1, which is a monitored vehicle MC, and the inter-vehicle distance D between the vehicles 100y1 and 100y2 is equal to or less than a threshold Dth (e.g., several meters). At this time, the driver of the vehicle 100y1 makes a lane change by turning the steering wheel significantly in the direction of the lane change, that is, by making the steering angle θ greater than a predetermined threshold θth (e.g., 30°), as shown in Fig. 9. When making a lane change in this manner, the driver of the vehicle 100x can determine whether the vehicle 100 is about to jump out of the congested lane by observing the steering angle θ of the front wheels of the vehicle 100 parked in the congested lane.

[0090] Based on the above findings, in this modification, the traveling_ECU 21 acquires the steering angle θ of the front wheels of the monitored vehicle MC and the inter-vehicle distance D between the monitored vehicle MC and the vehicle 100 ahead of the monitored vehicle MC, and is able to determine the likelihood TC of the monitored vehicle MC changing lanes based on the acquired steering angle θ and inter-vehicle distance D. Specifically, when the traveling_ECU 21 detects that the inter-vehicle distance D is equal to or less than a predetermined threshold Dth and that the steering angle θ of the monitored vehicle MC is greater than the predetermined threshold θth, it is able to calculate (predict) the likelihood TC of the monitored vehicle MC changing lanes. On the other hand, when the steering angle θ is equal to or less than the predetermined threshold θth, there is no likelihood that the vehicle 100y1 will change lanes. Therefore, when the traveling_ECU 21 detects that the steering angle θ is equal to or less than the predetermined threshold θth when the inter-vehicle distance D is equal to or less than the predetermined threshold Dth, it is able to set the likelihood TC of the monitored vehicle MC changing lanes to a small value (e.g., zero).

[0091] After calculating the predicted time Tp (step S108), the traveling_ECU 21 calculates the inter-vehicle distance D based on the vehicle information Db acquired from the traveling environment detection unit 11d or the traveling environment recognition unit 13c (step S112). The traveling_ECU 21 calculates the inter-vehicle distance D for each monitored vehicle MC. At this time, the traveling_ECU 21 may, for example, detect the vehicle 100 closest to the monitored vehicle MC among the multiple vehicles 100 located ahead of the monitored vehicle MC based on a distance image acquired from the traveling environment detection unit 11d, calculate the gap between the detected vehicle 100 and the monitored vehicle MC, and set the calculated gap as the inter-vehicle distance D. If the vehicle 100x is equipped with a ranging laser, the traveling_ECU 21 may, for example, detect the vehicle 100 closest to the monitored vehicle MC among the multiple vehicles 100 located ahead of the monitored vehicle MC based on a distance image acquired by the ranging laser.

[0092] The traveling_ECU 21 determines whether the inter-vehicle distance D is equal to or less than a predetermined threshold value Dth (step S113). The traveling_ECU 21 performs this determination for each monitored vehicle MC. As a result, if the inter-vehicle distance D is equal to or less than the predetermined threshold value Dth (step S113; Y), the traveling_ECU 21 acquires the steering angle θ of the front wheels of the monitored vehicle MC (step S114). The traveling_ECU 21 may acquire information on the steering angle θ of the front wheels of the monitored vehicle MC from the monitored vehicle MC, for example, through vehicle-to-vehicle communication via the transceiver 18. The traveling_ECU 21 may calculate the steering angle θ of the front wheels of the monitored vehicle MC based on, for example, a distance image obtained from the driving environment detection unit 11d.

[0093] The traveling_ECU 21 determines whether the steering angle θ exceeds a predetermined threshold θth (step S115). The traveling_ECU 21 determines the steering angle θ for the monitored vehicle MC whose inter-vehicle distance D is equal to or less than the predetermined threshold Dth. That is, the traveling_ECU 21 predicts the possibility of the monitored vehicle MC changing lanes based on the steering angle θ only when the steering angle θ is equal to or less than the predetermined threshold θth. As a result, if the steering angle θ exceeds the predetermined threshold θth (step S115; Y), the traveling_ECU 21 calculates the lane change possibility TC (step S119), as in the above embodiment. On the other hand, if the inter-vehicle distance D is greater than the predetermined threshold Dth (step S113; N) or if the steering angle θ is equal to or less than the predetermined threshold θth (step S115; N), the traveling_ECU 21 sets the lane change possibility TC to zero (step S116).

[0094] Thereafter, the traveling_ECU 21 determines whether the calculated or set lane change possibility TC is equal to or greater than a predetermined threshold value TCth (step S110). As a result, if there is a vehicle 100 whose lane change possibility TC is equal to or greater than the predetermined threshold value TCth (step S110; Y), the traveling_ECU 21 notifies the driver of the vehicle (host vehicle) 100x that there is a possibility that the vehicle 100 will suddenly appear in front of the vehicle (host vehicle) 100x (step S111). On the other hand, if the lane change possibility TC is less than the predetermined threshold value TCth (step S110; N), the traveling_ECU 21 executes step S101.

[0095] In this modification, unless the inter-vehicle distance D between the monitored vehicle MC and the vehicle 100 ahead of the monitored vehicle MC is equal to or less than a predetermined threshold Dth and the steering angle θ of the front wheels of the monitored vehicle MC exceeds a predetermined threshold θth, it is determined that there is no possibility of the monitored vehicle MC changing lanes. This makes it possible to avoid unnecessary notification to the driver of vehicle 100x when the possibility of the monitored vehicle MC changing lanes is low, or when the monitored vehicle MC and vehicle 100x are unlikely to come into contact with each other even if the monitored vehicle MC changes lanes.

[0096] In this modification, the possibility TC of the monitored vehicle MC changing lanes is predicted only when the inter-vehicle distance D between the monitored vehicle MC and the vehicle 100 ahead of the monitored vehicle MC is equal to or less than a predetermined threshold Dth and the steering angle θ of the front wheels of the monitored vehicle MC is equal to or less than a predetermined threshold θth. This allows the necessary calculations to be performed only when there is a possibility that the monitored vehicle MC will change lanes, thereby reducing the calculation load on the travel_ECU 21.

[0097] [Variation 3-2] In the above embodiment and its variations, the driving_ECU 21 may be configured to determine the possibility TC of the monitored vehicle MC changing lanes based on information (safety confirmation information Dc) as to whether the driver of the monitored vehicle MC is taking safety confirmation actions such as checking the rear using the side mirrors or visually.

[0098] Fig. 10 shows a modified example of the procedure for predicting a lane change in the cruise control system 1. Fig. 11 shows an example of a traffic situation in step S117 of Fig. 10 .

[0099] When the driver of the vehicle 100 in the congested lane intends to change lanes to an adjacent, open lane, the driver may, for example, check the rear by looking at the rearview mirror or side mirror, or by visually checking the rear. If such safety confirmation behavior by the driver of the vehicle 100 in the congested lane is observed, the vehicle 100 driven by that driver is likely to change lanes.

[0100] Based on the above findings, in this modification, the travel_ECU 21 is able to acquire information about the safety confirmation behavior of the monitored vehicle MC (safety confirmation information Dc) and determine the possibility TC of the monitored vehicle MC changing lanes based on the acquired safety confirmation information Dc. Specifically, when a safety confirmation behavior is observed in the monitored vehicle MC, the travel_ECU 21 is able to calculate the possibility TC of the monitored vehicle MC changing lanes based on the safety confirmation information Dc.

[0101] 11 , the vehicle 100x may acquire a stereo image including an area including the monitored vehicle MC upon starting a lane change, and may detect a safety confirmation behavior of the monitored vehicle MC based on the acquired stereo image. In this case, the traveling_ECU 21 may generate safety confirmation information Dc based on the detected safety confirmation behavior. The vehicle 100x may acquire the safety confirmation information Dc from the monitored vehicle MC, for example, through vehicle-to-vehicle communication via the transceiver 18.

[0102] The traveling_ECU 21 acquires the safety confirmation information Dc as described above (step S117). After acquiring the safety confirmation information Dc, the traveling_ECU 21 calculates the possibility TC of a lane change for each monitored vehicle MC based on the predicted time Tp and the safety confirmation information Dc (step S109). The traveling_ECU 21 determines whether a safety confirmation behavior is observed in the monitored vehicle MC based on the safety confirmation information Dc (step S118). As a result, if a safety confirmation behavior is observed in the monitored vehicle MC (step S118; Y), the traveling_ECU 21 corrects the lane change possibility TC calculated in step S109 to increase the lane change possibility TC (step S119). On the other hand, if a safety confirmation behavior is not observed in the monitored vehicle MC (step S118; N), the traveling_ECU 21 does not correct the lane change possibility TC calculated in step S109.

[0103] In this modification, the possibility TC of a lane change is calculated for each monitored vehicle MC based on the predicted time Tp and the safety confirmation information Dc. This makes it possible to avoid unnecessary notification to the driver of the vehicle 100x when the possibility of the monitored vehicle MC changing lanes is low.

[0104] In addition, in this modified example, the possibility TC of lane change is corrected based on the safety confirmation information Dc, so that when there is a high possibility of the monitored vehicle MC changing lanes, it is possible to reliably notify the driver of vehicle 100x.

[0105] In this modification, if the vehicle (host vehicle) 100x is equipped with lane keeping driving control (a following function) that maintains driving in the current driving lane, the driving_ECU 21 may be capable of correcting the lane change probability TC based on whether the following function is being used. For example, as shown in FIG. 12 , if the following function is being used (step S120; Y), the driving_ECU 21 corrects the lane change probability TC to decrease the lane change probability TC (step S121). On the other hand, if the following function is not being used (step S120; N), the driving_ECU 21 corrects the lane change probability TC calculated in step S109 to increase the lane change probability TC (step S119).

[0106] In this way, if the possibility of lane change TC is corrected based on whether or not the following function is used, it is possible to avoid unnecessary notification to the driver of vehicle 100x when the possibility of the monitored vehicle MC changing lanes is low.

[0107] [Variation 3-3] In the above embodiment and the variations thereof, the travel_ECU 21 may be configured to perform travel control based on the possibility TC of a lane change, as shown in FIG. 13 (step S122). In this case, instead of notifying the driver of the vehicle (host vehicle) 100x that the vehicle 100 may change lanes and jump out in front of the vehicle (host vehicle) 100x, or in addition to notifying the driver, the travel_ECU 21 may be configured to perform braking control on the travel of the vehicle 100 (step S123). In this case, the driver of the vehicle 100x can be notified early of the presence of the vehicle 100 that may jump out from the congested lane by changing lanes when passing through the congested lane, and it is also possible to reliably avoid a collision accident that may occur when passing through the congested lane.

[0108] [Variation 3-4] In the above embodiment and its variations, the predicted time tp is not limited to the time (first predicted time) required for the vehicle 100x to reach a position in the lane after the lane change that corresponds to the side of the monitored vehicle MC from the time when the vehicle 100x starts changing lanes. The predicted time tp may be, for example, a time that has a predetermined correlation with the first predicted time. The predicted time tp may be, for example, a time (time) when the start timing of the first predicted time is slightly shifted from the time when the vehicle 100x starts changing lanes.

[0109] In the above embodiment and its modified examples, the predicted time tp is not limited to the time (second predicted time) required from the time (time) when the lane change is completed to the time when the vehicle MC reaches a position on the lane after the lane change that corresponds to the side of the monitored vehicle MC. The predicted time tp may be, for example, a time that has a predetermined correlation with the second predicted time. The predicted time tp may be, for example, a time (time) when the start timing of the second predicted time is slightly shifted from the time (time) when the lane change is completed.

[0110] 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.

[0111] Furthermore, for example, the present disclosure may be configured as follows: (1) A driving assistance device including a control unit capable of predicting a likelihood that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane, when at least a first lane of two or more driving lanes in each direction is a congested lane and at least a second lane of the driving lanes adjacent to the first lane is an uncongested lane, wherein the control unit is capable of: acquiring traffic data on the driving lane, the congested lane, the uncongested lane, the first vehicle, and the second vehicle; predicting, based on the traffic data, a time required for the first vehicle to reach a position in the second lane that corresponds to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and predicting the likelihood that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction. (2) The driving assistance device described in (1), wherein the control unit is capable of acquiring start data regarding the start of a lane change by the first vehicle, and setting, based on the start data, the predicted time to a time required for the first vehicle to reach a position in the second lane corresponding to the side of the second vehicle, from when the first vehicle started to change lanes, or a time having a predetermined correlation with this time. (3) The driving assistance device described in (1), wherein the control unit is capable of acquiring data including completion data regarding the completion of a lane change by the first vehicle, and setting, based on the completion data, the predicted time to a time required for the first vehicle to reach a position in the second lane corresponding to the side of the second vehicle, from when the first vehicle completed the lane change, or a time having a predetermined correlation with this time. (4) The driving assistance device described in any one of (1) to (3), wherein the control unit is capable of acquiring steering angle data regarding the steering angle of front wheels of the second vehicle, and determining that there is no possibility that the second vehicle will change lanes unless the steering angle data exceeds a first threshold.(5) The driving assistance device according to (4), wherein the control unit is capable of acquiring inter-vehicle distance data regarding a distance between the second vehicle and a vehicle ahead of the second vehicle, and predicting a possibility of the second vehicle changing lanes based on the steering angle data only when the inter-vehicle distance data is equal to or less than a second threshold. (6) The driving assistance device according to any one of (1) to (5), wherein the control unit is capable of acquiring safety confirmation data indicating whether a driver of the second vehicle has performed a safety confirmation action of checking the side mirrors or the rear of the second vehicle, and predicting a possibility of the second vehicle changing lanes from the congested lane to the second lane based on the safety confirmation data and the predicted time. (7) The driving assistance device according to any one of (1) to (6), wherein the control unit is capable of generating a control signal to notify the driver of the first vehicle that the second vehicle is likely to change lanes when a predetermined condition is satisfied. (8) The driving assistance device according to any one of (1) to (7), wherein the control unit is capable of performing braking control on the traveling of the first vehicle when a possibility of the second vehicle changing lanes satisfies a predetermined condition. (9) The driving assistance device according to any one of (1) to (8), wherein the control unit is capable of continuing to acquire data about the second vehicle while a possibility of the second vehicle changing lanes satisfies a predetermined condition.(10) A vehicle including a control unit capable of predicting the possibility that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane, when at least a first lane of two or more driving lanes on each side is a congested lane and at least a second lane of the driving lanes adjacent to the first lane is an uncongested lane, wherein the control unit is capable of: acquiring traffic data about the driving lane, the congested lane, the uncongested lane, the first vehicle, and the second vehicle; predicting, based on the traffic data, the time required for the first vehicle to reach a position in the second lane corresponding to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and predicting the possibility that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction. (11) A driving assistance method capable of predicting the possibility that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane in a road with two or more lanes in each direction, where at least a first lane is a congested lane and at least a second lane of the driving lanes adjacent to the first lane is an uncongested lane, the driving assistance method includes: acquiring traffic data about the driving lane, the congested lane, the uncongested lane, the first vehicle, and the second vehicle; predicting, based on the traffic data, a time required for the first vehicle to reach a position in the second lane corresponding to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and predicting the possibility that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction.

[0112] 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 a possibility that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane, when at least a first lane of two or more driving lanes on one side is a congested lane and at least a second lane of the driving lanes adjacent to the first lane is an uncongested lane, wherein the control unit is capable of: acquiring traffic data on the driving lanes, the congested lane, the uncongested lane, the first vehicle, and the second vehicle; predicting, based on the traffic data, a time required for the first vehicle to reach a position in the second lane equivalent to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and predicting the possibility that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction.

2. The driving assistance device according to claim 1, wherein the control unit is capable of: acquiring start data regarding the initiation of a lane change by the first vehicle; and determining, based on the start data, the predicted time as the time required from when the first vehicle starts to change lanes until it reaches a position in the second lane corresponding to the side of the second vehicle, or a time having a predetermined correlation with this time.

3. The driving assistance device according to claim 1, wherein the control unit is capable of: acquiring data including completion data regarding the completion of a lane change by the first vehicle; and determining, based on the completion data, the predicted time as a time required from when the first vehicle completes the lane change to when the first vehicle reaches a position in the second lane corresponding to the side of the second vehicle, or a time having a predetermined correlation with this time.

4. The driving assistance device of claim 1, wherein the control unit is capable of acquiring steering angle data regarding the steering angle of the front wheels of the second vehicle, and determining that there is no possibility of the second vehicle changing lanes unless the steering angle data exceeds a first threshold value.

5. The driving assistance device according to claim 4, wherein the control unit is capable of obtaining distance data regarding the distance between the second vehicle and a vehicle in front of the second vehicle, and predicting the possibility of the second vehicle changing lanes based on the steering angle data only when the distance data is equal to or less than a second threshold value.

6. The driving assistance device of claim 1, wherein the control unit is capable of obtaining safety confirmation data indicating whether or not the driver of the second vehicle has performed a safety confirmation action of checking the side mirror or rear of the second vehicle, and predicting the possibility that the second vehicle will change lanes from the congested lane to the second lane based on the safety confirmation data and the predicted time.

7. The driving assistance device according to claim 1, wherein the control unit is capable of generating a control signal for notifying the driver of the first vehicle of the possibility of the second vehicle changing lanes when a predetermined condition is satisfied that the second vehicle will change lanes.

8. The driving assistance device according to claim 1, wherein the control unit is capable of performing braking control on the traveling of the first vehicle when a possibility of the second vehicle changing lanes satisfies a predetermined condition.

9. The driving assistance device according to claim 1, wherein the control unit is capable of continuing to acquire data about the second vehicle while a possibility of the second vehicle changing lanes satisfies a predetermined condition, and performing driving control of the first vehicle based on the data that is being acquired.

10. A vehicle comprising a control unit capable of predicting the possibility that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane, when at least a first lane of two or more travel lanes on one side is a congested lane and at least a second lane of the travel lanes adjacent to the first lane is an uncongested lane, wherein the control unit is capable of: acquiring traffic data on the travel lanes, the congested lane, the uncongested lane, the first vehicle, and the second vehicle; predicting, based on the traffic data, a time required for the first vehicle to reach a position in the second lane equivalent to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and predicting the possibility that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction.

11. A driving assistance method capable of predicting the possibility that a second vehicle located in the congested lane will change lanes from the congested lane to the second lane when a first vehicle changes lanes to the second lane, when at least a first lane of two or more driving lanes in each direction is a congested lane and at least a second lane of the driving lanes adjacent to the first lane is an uncongested lane, the driving assistance method comprising: acquiring traffic data on the driving lanes, the congested lane, the uncongested lane, the first vehicle, and the second vehicle; predicting, based on the traffic data, a time required for the first vehicle to reach a position in the second lane equivalent to the side of the second vehicle after changing lanes, or a time having a predetermined correlation with this time; and predicting the possibility that the second vehicle will change lanes from the congested lane to the second lane, based on the predicted time obtained by the prediction.

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