Driving assistance systems

Abstract

To provide a driving support device that can properly perform driving support for enabling an own vehicle to avoid collision, when the other vehicle travelling on a road having two or more lanes intersecting with a road on which the own vehicle is travelling changes a lane to the lane close to the road on which the own vehicle is travelling.SOLUTION: A driving support device comprises a recognition sensor and a processor. The recognition senor includes a camera that photographs the other vehicle travelling on a road having two or more lanes intersecting with a road on which an own vehicle is travelling, which recognizes a situation around the own vehicle. The processor executes driving support processing for enabling the own vehicle to avoid collision with the other vehicle. The processor predicts whether the other vehicle may change a lane from a far-lane to a near-lane, when viewed from the own vehicle or not, on the basis of travelling information on the other vehicle which is detected by the recognition sensor. The processor executes the driving support processing in a mode according to the predicted result.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present disclosure relates to a driving support device applied to a vehicle.

Background Art

[0002] Patent Document 1 discloses a driving support device. This driving support device calculates the movement trajectory of a moving object moving on a road that intersects with the traveling road of the host vehicle. Then, the driving support device determines whether there is a possibility that the moving object may collide with the host vehicle by comparing the calculated movement trajectory with the movement trajectory of the host vehicle.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When the road intersecting with the traveling road of the host vehicle is a road with two or more lanes, another vehicle traveling on the road may change lanes from the lane farther from the host vehicle to the lane closer to the host vehicle. When another vehicle makes such a lane change, it is required to appropriately execute driving support to avoid a collision between the host vehicle and the other vehicle.

[0005] The present disclosure has been made in view of the above problems, and an object thereof is to provide a driving support device that can appropriately perform driving support for collision avoidance when another vehicle traveling on a road with two or more lanes intersecting with the traveling road of the host vehicle changes lanes to a lane closer to the host vehicle.

Means for Solving the Problems

[0006] The driver assistance system according to this disclosure comprises a recognition sensor and a processor. The recognition sensor includes a camera that captures images of other vehicles on a road with two or more lanes that intersects with the vehicle's path, and recognizes the situation around the vehicle. The processor performs driver assistance processing to help avoid collisions between the vehicle and other vehicles. Based on the other vehicle driving information, which is driving information of other vehicles detected by the recognition sensor, the processor predicts whether or not the other vehicle will change lanes from the lane further away from the vehicle to the lane closer to it. The processor performs driver assistance processing in a manner corresponding to the result of the above prediction.

[0007] Other vehicle information may include information indicating whether or not other vehicles' turn signals are flashing.

[0008] Other vehicle information may include information indicating the distance of other vehicles to the lane marking closest to the vehicle's own lane among the lane markings that demarcate the other vehicles' driving lanes.

[0009] The vehicle may include an actuator that controls at least one of the vehicle's driving and braking, and an HMI device that provides notifications to the vehicle's driver. The result of the above prediction may be a lane change probability, which is the probability that another vehicle is predicted to make the lane change. The driving assistance process may include a first process that controls the actuator to suppress the vehicle's forward movement, and a second process that controls the HMI device to provide notifications regarding the warning for collision avoidance. The processor may then execute the first process if the lane change probability is above a threshold, and execute the second process if the lane change probability is below the threshold.

[0010] The processor may perform the above-mentioned prediction under low-speed conditions where the vehicle's speed is below a predetermined speed, and may execute driving assistance processing in a manner corresponding to the result of the prediction. [Effects of the Invention]

[0011] According to the driver assistance device described herein, the processor predicts whether or not another vehicle will change lanes in the manner described above, based on other vehicle driving information detected by a recognition sensor. The processor then executes driver assistance processing to help avoid a collision between the vehicle and the other vehicle in a manner corresponding to the result of the prediction. This enables appropriate driver assistance to avoid a collision when another vehicle traveling on a road with two or more lanes that intersects the vehicle's path changes lanes to the lane closest to the vehicle. [Brief explanation of the drawing]

[0012] [Figure 1] This diagram schematically shows an example of the configuration of a vehicle equipped with a driver assistance device according to an embodiment. [Figure 2] This diagram illustrates the overview and challenges of FCTA. [Figure 3] This figure shows an example of a scene in which the driver assistance process PR, based on the prediction of another vehicle's lane change LC according to the embodiment, is executed. [Figure 4] This is a flowchart relating to the driver assistance process PR based on the prediction of lane change LC of other vehicles according to the embodiment. [Modes for carrying out the invention]

[0013] Embodiments of this disclosure will be described below with reference to the attached drawings. In each drawing, elements common to all figures are denoted by the same reference numerals, and redundant explanations are omitted or simplified.

[0014] 1. Example of vehicle configuration Figure 1 is a schematic diagram showing an example of the configuration of a vehicle equipped with a driver assistance system according to an embodiment. The vehicle 1 shown in Figure 1 includes an electronic control unit (ECU) 10, a recognition sensor 20, an HMI (Human Machine Interface) device 30, a drive unit 40, and a braking unit 50. Note that vehicle 1 may be an autonomous driving vehicle.

[0015] The ECU 10 is a computer that controls the vehicle 1. The ECU 10 includes one or more processors (hereinafter simply referred to as "processors") 12 and one or more storage devices (hereinafter simply referred to as "storage devices") 14. The processor 12 performs various processes related to the control of the vehicle 1. The storage device 14 stores various information necessary for the processing by the processor 12. Examples of storage devices 14 include volatile memory, non-volatile memory, HDD (Hard Disk Drive), SSD (Solid State Drive), etc. The processor 12 performs various processes by executing various computer programs. The various computer programs are stored in the storage device 14 or recorded on a computer-readable recording medium. Note that the ECU 10 may be composed of multiple ECUs.

[0016] The recognition sensor 20 recognizes the surrounding conditions of the vehicle (vehicle 1). The recognition sensor 20 is electrically connected to the ECU 10. As an example, the recognition sensor 20 includes radars 22, 24, and 26 and a front camera 28. The radars 22, 24, and 26 are, for example, millimeter-wave radars. The central front radar 22 detects objects in the area in front of vehicle 1. The right front radar 24 detects objects in the right front area of ​​vehicle 1. The left front radar 26 detects objects in the left front area of ​​vehicle 1. The front camera 28 captures images of the area in front of vehicle 1.

[0017] The HMI device 30 provides alerts to the driver of vehicle 1. The HMI device 30 includes, for example, a display for attracting attention visually. The display is, for example, a display mounted on the instrument panel of vehicle 1, or a head-up display (HUD) that displays information on the windshield 2 of vehicle 1. The HMI device 30 also includes, for example, at least one of a buzzer and a speaker for attracting attention auditorily, along with the display. The HMI device 30 is controlled by the ECU 10 (processor 12).

[0018] The drive device 40 generates the driving force of the vehicle 1. The drive device 40 includes, for example, at least one of an electric motor and an internal combustion engine for driving the vehicle 1. The braking device 50 generates the braking force of the vehicle 1. The braking device 50 is It includes a brake actuator for braking the vehicle 1. Note that at least one of the electric motor and the internal combustion engine corresponds to an example of the "actuator" according to the present disclosure. Similarly, the brake actuator corresponds to another example of the "actuator" according to the present disclosure.

[0019] In an example of the vehicle 1 having the above-described configuration, the "driving support device" according to the present disclosure includes the ECU 10 including the above-described processor 12, the recognition sensor 20, and the HMI device 30.

[0020] 2. Driving support for collision avoidance 2-1. Problems of FCTA As one of the prior arts for assisting the driving of the driver of the host vehicle to avoid collisions with moving objects such as other vehicles, there is FCTA (Front Cross Traffic Alert). FCTA is executed when a predetermined operating condition is satisfied. The operating condition includes, for example, that the speed of the host vehicle is less than or equal to a predetermined speed (for example, 15 km / h).

[0021] FIG. 2(A) is a diagram for explaining the outline of FCTA. FIG. 2(A) illustrates a one-lane road 104 on one side that intersects with the traveling road 102 of the host vehicle 100. The road 104 has an intersecting lane 106 and an intersecting lane 108. The intersecting lane 106 is located on the side closer to the traveling road 102. The intersecting lane 108 is the oncoming lane of the intersecting lane 106 and is located on the side farther from the traveling road 102. In FIG. 2(A), another vehicle 110 is traveling in the intersecting lane 106, and another vehicle 112, which is the oncoming vehicle of the other vehicle 110, is traveling in the intersecting lane 108.

[0022] In FCTA, when vehicle 100 is about to enter an intersecting lane 106 or 108, the ECU of vehicle 100 uses recognition sensors such as radar to detect the approach of another vehicle 110 or 112 to vehicle 100. If such approach is detected, the ECU issues a warning to the driver of vehicle 100. This warning is issued using an HMI (Human-Machine Interface) device.

[0023] For more details, see Figure 2(A) to This represents the vehicle 100, which is starting from a standstill or traveling at a low speed on lane 102 and attempting to merge into intersecting lane 106 or 108. According to FCTA, if another vehicle 110 is present when the vehicle 100 is attempting to turn left and merge into intersecting lane 106, the approach of the other vehicle 110 will be detected and a warning regarding the approach will be issued. On the other hand, if another vehicle 112 is present when the vehicle 100 is attempting to turn right and merge into intersecting lane 108, the approach of the other vehicle 112 will be detected and a warning regarding the approach will be issued.

[0024] Figure 2(B) is a diagram illustrating the challenges of FCTA. Figure 2(B) illustrates a two-lane road 120 intersecting the roadway 102 of a vehicle 100. Road 120 is, for example, a main road and includes two intersecting lanes 122 and 124 and a median strip 126. Intersecting lane 122 is located on the side closer to the roadway 102. Intersecting lane 124 is located on the side further from the roadway 102 and is adjacent to intersecting lane 122. Intersecting lanes 122 and 124 are lanes in the same direction.

[0025] In the example shown in Figure 2(B), vehicle 100 is about to turn left and enter (merge) into intersecting lane 122. Another vehicle 128, traveling in intersecting lane 124, is about to change lanes from the intersecting lane 124, which is farther from vehicle 100, to the intersecting lane 122, which is closer to vehicle 100, as it passes near the roadway 102. This type of lane change, that is, a lane change by another vehicle from the lane farther from the vehicle to the lane closer to the vehicle, will be referred to below as a "lane change LC".

[0026] As illustrated in Figure 2(B), another vehicle (e.g., other vehicle 128) may perform a lane change (LC) into the intersecting lane (e.g., intersecting lane 122) that vehicle 100 is attempting to enter. Under existing FCTA (Forward Cross Traffic Alert) systems, it may not be possible or possible to provide timely warnings regarding the approach of other vehicles performing such lane changes.

[0027] 2-2. Collision avoidance based on predicting lane changes by other vehicles In view of the above-mentioned issues, in this embodiment, the ECU 10 (processor 12) predicts whether or not another vehicle will perform a lane change LC from the lane furthest from the vehicle 1 to the lane closer to it, based on the other vehicle driving information VI. Then, the ECU 10 executes the "driving support process PR" in a manner corresponding to the prediction.

[0028] Figure 3 shows an example of a scene in which the driving assistance process PR based on the prediction of another vehicle's lane change LC according to the embodiment is executed. Similar to Figure 2(B), Figure 3 shows another vehicle 128 making a lane change LC from the intersecting lane 124 that is farther away from the vehicle 1 to the intersecting lane 122 that is closer. Figure 3 also shows the field of view of the right front radar 24 (dashed line) and the field of view of the front camera 28 (solid line).

[0029] Other vehicle driving information VI is driving information related to the driving of other vehicles 128 and is detected by the recognition sensor 20. Other vehicle driving information VI includes, for example, radar information and camera information. Each of the recognition sensors 20 acquires other vehicle driving information VI at predetermined intervals and supplies it to the ECU 10.

[0030] Radar information is acquired using the right-front radar 24 and the left-front radar 26. The radar information includes, for example, the vehicle speed and lateral speed of other vehicles 128.

[0031] Camera information is obtained by analyzing images captured by the front camera 28. The camera information includes, for example, information indicating whether the turn signals 128a or 128b of the other vehicle 128 are flashing (turn signal information). The camera information also includes, for example, information indicating the distance D of the other vehicle 128 to the lane marking (e.g., white line) that is closer to the vehicle 1 (in Figure 3, lane marking 130) of the lane the other vehicle 128 is traveling in (in Figure 3, intersecting lane 124) (lane marking information). Since the turn signal information and lane marking information cannot be obtained using radars 22-26, they are obtained using, for example, the front camera 28. The camera information may include only either the turn signal information or the lane marking information.

[0032] In this embodiment, the prediction of lane changes (LC) by other vehicles is performed using a machine learning model based on other vehicle driving information VI. An example of such a machine learning model is an HMM (Hidden Markov Model). According to the HMM, the result of the above prediction can be obtained in the form of the probability (%) that the other vehicle is predicted to perform a lane change (LC). Hereinafter, this probability will be referred to as "lane change probability P". The HMM has been trained in advance using data from various traffic scenarios. The ECU10 implements this trained HMM.

[0033] As described above, the HMM is configured to receive other vehicle driving information VI as input and output a lane change probability P. More specifically, the HMM outputs a lane change probability P at predetermined intervals corresponding to the other vehicle driving information VI supplied from the recognition sensor 20. Therefore, when other vehicles present around the vehicle 1 within the range recognizable by the recognition sensor 20 actually begin to exhibit behavior that leads to a lane change LC (for example, other vehicle 128 in Figure 3), the lane change probability P output from the HMM increases. On the other hand, for example, when other vehicles present around the vehicle 1 stop exhibiting behavior that leads to a lane change LC, the lane change probability P decreases. Thus, the lane change probability P for the same other vehicle can change over time.

[0034] In addition, regarding the turn signal information mentioned above, the flashing of the turn signal (more specifically, the turn signal on the side closer to the vehicle 1) 128a or 128b of another vehicle 128 acts to increase the probability P of a lane change in the HMM. In the example shown in Figure 3, the flashing of the left turn signal 128b of the other vehicle 128 acts to increase the probability P of a lane change LC to the left. That is, when the turn signal 128b is flashing, the HMM outputs a higher probability P of a lane change compared to when the turn signal 128b is not flashing.

[0035] Furthermore, a decrease in the distance D in the aforementioned lane marking information acts to increase the probability P of lane changes in the HMM. That is, when the distance D decreases, the HMM outputs a higher probability P of lane changes compared to when the distance D increases.

[0036] The driver assistance process PR is performed by the ECU 10 to avoid a collision between the vehicle 1 and another vehicle 128. Specifically, the driver assistance process PR includes a first process PR1 and a second process PR2.

[0037] The first process PR1 is a process of controlling the actuator (an actuator included in at least one of the drive unit 40 and the braking unit 50) to suppress the forward movement of the vehicle 1. Here, "forward movement" includes the starting of the vehicle 1.

[0038] More specifically, the first process PR1 includes, for example, automatically reducing the output of an actuator (internal combustion engine or electric motor) included in the drive unit 40 in order to suppress the forward movement of the vehicle 1, such as starting. The first process PR1 also includes, for example, automatically braking the vehicle 1 by controlling a brake actuator included in the braking unit 50 in order to suppress the forward movement of the vehicle 1, such as starting.

[0039] The second process PR2 is a process that controls the HMI device 30 to provide a warning to avoid a collision between the vehicle 1 and the other vehicle 128. For example, the warning provided by the second process PR2 relates to a warning using at least one of the buzzer and speaker of the HMI device 30. Alternatively, the warning may relate to a warning from the display of the HMI device 30. Or, the warning may relate to both of these warnings. More specifically, the warning encourages, for example, the vehicle 1 to refrain from moving forward (including starting).

[0040] The driver assistance process PR based on the above prediction of lane change LC is executed, for example, as follows: The ECU 10 executes the first process PR1 if the lane change probability P is greater than or equal to a predetermined threshold TH1. The ECU 10 then executes the second process PR2 if the lane change probability P is less than the threshold TH1.

[0041] Furthermore, if, after the start of the driver assistance processing PR, the other vehicle for which the lane change probability P is output moves out of the range recognizable by the recognition sensor 20 of the vehicle 1, the lane change probability P for that other vehicle will no longer be obtained. As a result, the driver assistance processing PR for that other vehicle will be terminated.

[0042] Furthermore, the example shown in Figure 3 above depicts a scenario in which vehicle 1 is about to enter a "two-lane road 120" that intersects with its own vehicle's driving path 102. However, the prediction of lane change LCs according to this embodiment may also be performed for other vehicles traveling on "roads with three or more lanes in each direction" that intersect with the vehicle's driving path. For example, on a three-lane road, the prediction of the lane change probability P may be performed for a lane change LC of another vehicle from the intersecting lane furthest from vehicle 1 to the central intersecting lane. Moreover, even if the road intersecting with the vehicle's driving path is a "one-lane road," other vehicles traveling on that road may make a lane change LC into the oncoming lane to overtake a preceding vehicle. For this reason, the prediction of lane change LCs may also be performed for lane change LCs of other vehicles on such one-lane roads. Furthermore, the example shown in Figure 3 depicts a scene in which vehicle 1 turns left to enter a road 120 that intersects with its own driving path 102. However, the driver assistance according to this embodiment can also be applied to a scene in which the vehicle turns right to enter a road that intersects with its own driving path, provided that the recognition sensor is capable of recognizing other vehicles.

[0043] Figure 4 is a flowchart relating to the driver assistance process PR based on the prediction of another vehicle's lane change LC according to the embodiment. The process in this flowchart is repeatedly executed at predetermined intervals when predetermined operating conditions are met. These operating conditions include, for example, that the speed of the vehicle 1 is less than or equal to a predetermined speed (for example, 15 km / h) (i.e., that the low-speed condition is met).

[0044] In step S100, the ECU 10 (processor 12) acquires the other vehicle driving information VI detected by the recognition sensor 20. As already explained, the other vehicle driving information VI includes radar information and camera information.

[0045] Next, in step S102, the ECU 10 determines whether the output of the recognition sensor 20 is normal. If the recognition sensor 20 (more specifically, at least one of the radars 22-26 and the front camera 28) shows an abnormal output, the process proceeds to return.

[0046] On the other hand, if the output of the recognition sensor 20 is normal in step S102, the ECU 10 acquires the output of the HMM in step S104. That is, the lane change probability P corresponding to the other vehicle driving information VI acquired in step S100 is acquired.

[0047] Next, in step S106, the ECU 10 determines whether the HMM output is normal or not. Specifically, for example, if the value of the lane change probability P is a value predetermined to be output when the HMM output is not normal, the determination result in step S106 is No. As a result, the process proceeds to return. Also, if there are no other vehicles within the range recognizable by the recognition sensor 20, the other vehicle driving information VI of those other vehicles cannot be obtained. In other words, the HMM input information is insufficient. Even under these circumstances, the HMM cannot output the lane change probability P appropriately, so the determination result in step S106 is No. As a result, the process proceeds to return.

[0048] On the other hand, if the HMM output is normal in step S106, the process proceeds to step S108. In step S108, the ECU 10 determines whether the lane change probability P obtained in step S104 is greater than or equal to the threshold TH1. The threshold TH1 is an arbitrary value determined in advance, such as 50%, 60%, or 70%.

[0049] If the lane change probability P in step S108 is greater than or equal to the threshold TH1, the ECU 10 executes the first process PR1 in step S110. This controls an actuator included in at least one of the drive unit 40 and the braking unit 50 to suppress the forward movement (including starting) of the vehicle 1 in order to avoid collision with other vehicles.

[0050] On the other hand, when the lane change probability P is less than the threshold value TH1 in step S108, the ECU 10 executes the second process PR2 in step S112. Thereby, the HMI device 30 is controlled to notify the driver of the host vehicle 1 of a warning regarding avoidance of collision with other vehicles.

[0051] In addition, when the determination result in step S108 is No, the ECU 10 may execute the following process. That is, the ECU 10 may determine whether the lane change probability P is equal to or greater than a predetermined threshold value TH2. The threshold value TH2 is smaller than the threshold value TH1 and is a value greater than 0%. The threshold value TH2 is, for example, a few percent or 20%. Then, when the lane change probability P is equal to or greater than the threshold value TH2 and less than the threshold value TH1 (TH2 ≤ P < TH1), the ECU 10 may execute the process of step S112. On the other hand, when the lane change probability P is less than the threshold value TH2 (P < TH2), the ECU 10 may execute a process for notifying a warning with a lower degree of warning than the second process PR2 (step S112). For example, as the process, the ECU 10 may perform only a display for warning using the display of the HMI device 30 without notification by sound or voice. Alternatively, for example, the ECU 10 may determine that the lane change probability P is sufficiently low and may not perform the warning itself.

[0052] 3. Effects As described above, according to the present embodiment, the ECU 10 predicts whether or not another vehicle will perform a lane change LC based on the other vehicle running information VI detected by the recognition sensor 20. Thereby, it becomes possible to evaluate the risk of collision between the host vehicle 1 and other vehicles at an early stage. And the ECU 10 executes the driving support process PR in a manner corresponding to the result of the prediction. Thereby, when the host vehicle 1 is about to enter a road with two or more lanes intersecting the traveling road of the host vehicle 1, it becomes possible to appropriately perform driving support for collision avoidance for other vehicles that are about to perform a lane change LC in the intersection lane closer to the host vehicle 1.

[0053] More specifically, according to this embodiment, the lane change probability P is used as information indicating the result of the above prediction. The content of the driving support process PR is changed depending on whether the lane change probability P is equal to or greater than the threshold TH1. That is, if the lane change probability P is less than the threshold TH1, a second process PR2 is executed which controls the HMI device 30 to provide a warning regarding collision avoidance with other vehicles. On the other hand, if the lane change probability P is equal to or greater than the threshold TH1, a first process PR1 is executed which controls the actuator to suppress the forward movement of the vehicle 1. In other words, a process is executed to more actively avoid collisions because the lane change probability P is high. Thus, according to this embodiment, the driving support process PR can be executed in an appropriate manner depending on whether the lane change probability P is high or low.

[0054] Furthermore, according to this embodiment, the other vehicle driving information VI (camera information) used to predict the lane change LC of other vehicles includes information indicating whether or not the turn signals of other vehicles are flashing (turn signal information). This makes it possible to significantly improve the accuracy of predicting lane change LC.

[0055] Furthermore, according to this embodiment, the other vehicle driving information VI (camera information) includes information (lane marking information) indicating the distance D of the other vehicle to the lane marking closest to the vehicle among the lane markings that demarcate the other vehicle's driving lane. This makes it possible to significantly improve the accuracy of predicting lane changes LC. [Explanation of symbols]

[0056] 1 Vehicle (own vehicle), 10 Electronic Control Unit (ECU), 12 Processor, 14 Memory device, 20 Recognition sensor, 22 Center front radar, 24 Right front radar, 26 Left front radar, 28 Front camera, 30 HMI device, 40 Drive system, 50 Braking system, 102 Own vehicle's lane, 106, 108, 122, 124 Intersecting lanes, 110, 112, 128 Other vehicles, 128a, 128b Other vehicles' turn signals, 130 Lane markings closest to the own vehicle

Claims

1. The system includes a camera that captures images of other vehicles on roads with two or more lanes that intersect with the vehicle's path, and a recognition sensor that recognizes the surrounding conditions of the vehicle. A processor that performs driving assistance processing to help avoid collisions between the vehicle itself and other vehicles, Equipped with, The aforementioned processor, Based on the other vehicle driving information, which is the driving information of the other vehicle detected by the recognition sensor, a prediction is made as to whether the other vehicle will change lanes from the lane further away from the vehicle to the lane closer to it. The driving support process is executed in a manner corresponding to the results of the prediction, The aforementioned information on other vehicles includes information indicating whether or not the turn signals of the other vehicles are flashing. Driving assistance system.

2. The system includes a camera that captures images of other vehicles on roads with two or more lanes that intersect with the vehicle's path, and a recognition sensor that recognizes the surrounding conditions of the vehicle. A processor that performs driving assistance processing to help avoid collisions between the vehicle itself and other vehicles, Equipped with, The aforementioned processor, Based on the other vehicle driving information, which is the driving information of the other vehicle detected by the recognition sensor, a prediction is made as to whether the other vehicle will change lanes from the lane further away from the vehicle to the lane closer to it. The driving support process is executed in a manner corresponding to the results of the prediction, The aforementioned other vehicle driving information includes information indicating the distance of the other vehicle to the lane marking closest to the vehicle in question among the lane markings that demarcate the other vehicle's driving lane. Driving assistance system.

3. The system includes a camera that captures images of other vehicles on roads with two or more lanes that intersect with the vehicle's path, and a recognition sensor that recognizes the surrounding conditions of the vehicle. A processor that performs driving assistance processing to help avoid collisions between the vehicle itself and other vehicles, Equipped with, The aforementioned processor, Based on the other vehicle driving information, which is the driving information of the other vehicle detected by the recognition sensor, a prediction is made as to whether the other vehicle will change lanes from the lane further away from the vehicle to the lane closer to it. The driving support process is executed in a manner corresponding to the results of the prediction, The vehicle includes an actuator that controls at least one of the driving and braking of the vehicle, and an HMI device that provides notifications to the driver of the vehicle. The result of the above prediction is the lane change probability, which is the probability that the other vehicle is predicted to make the lane change. The aforementioned driver assistance process is: A first process of controlling the actuator to suppress the forward movement of the vehicle, A second process that controls the HMI device to provide notification regarding the warning for collision avoidance, Includes, The processor executes the first process if the probability of changing lanes is equal to or greater than a threshold, and executes the second process if the probability of changing lanes is less than the threshold. Driving assistance system.

4. The system includes a camera that captures images of other vehicles on roads with two or more lanes that intersect with the vehicle's path, and a recognition sensor that recognizes the surrounding conditions of the vehicle. A processor that performs driving assistance processing to help avoid collisions between the vehicle itself and other vehicles, Equipped with, The aforementioned processor, Based on the other vehicle driving information, which is the driving information of the other vehicle detected by the recognition sensor, a prediction is made as to whether the other vehicle will change lanes from the lane further away from the vehicle to the lane closer to it. The driver assistance process is executed in a manner corresponding to the results of the prediction, The processor performs the prediction under low-speed conditions where the vehicle's speed is below a predetermined speed, and executes the driving support process in a manner corresponding to the result of the prediction. Driving assistance system.

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