Driving control device, driving control method, and program
The driving control device improves safety by recognizing and predicting patterns on the road surface from surrounding vehicles, enabling proactive vehicle control to avoid hazards.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- TOYOTA JIDOSHA KK
- Filing Date
- 2023-11-30
- Publication Date
- 2026-06-30
Smart Images
Figure 0007882239000001 
Figure 0007882239000002 
Figure 0007882239000003
Abstract
Description
Technical Field
[0001] The present disclosure relates to a driving control device, a driving control method, and a program.
Background Art
[0002] Patent Document 1 describes that a sensing system including a camera for photographing a road surface and an arithmetic processing unit is mounted on a vehicle (host vehicle), that a pattern drawn on the road surface by another traffic participant (e.g., a surrounding vehicle or the like) is captured by the camera, that the arithmetic processing unit detects the states of the host vehicle and other traffic participants based on the pattern captured in the image of the camera, and that the vehicle (host vehicle) equipped with the sensing system controls at least one of steering, accelerator, and brake according to the output of the sensing system.
Prior Art Documents
Patent Documents
[0003]
Patent Document 1
Summary of the Invention
Problems to be Solved by the Invention
[0004] By the way, in the technique described in Patent Document 1, the pattern drawn on the road surface by another traffic participant does not predict the future behavior of the other traffic participant (e.g., the surrounding vehicle as another traffic participant reversing, the door of the surrounding vehicle (specifically, the surrounding vehicle with the door closed) as another traffic participant opening, etc.). Therefore, with the technique described in Patent Document 1, the host vehicle cannot predict the future behavior of other traffic participants based on the pattern drawn on the road surface by other traffic participants. As a result, with the technique described in Patent Document 1, the driving of the host vehicle cannot be appropriately controlled based on the pattern drawn on the road surface by other traffic participants, and the driving safety of the host vehicle cannot be sufficiently improved.
[0005] In view of the above, the purpose of this disclosure is to provide a driving control device, a driving control method, and a program that can sufficiently improve the driving safety of the vehicle. [Means for solving the problem]
[0006] (1) One aspect of the present disclosure is a driving control device comprising: an image recognition unit that performs image recognition of a pattern drawn on the road surface by light emitted from surrounding vehicles; a prediction unit that predicts the behavior of the surrounding vehicles based on the results of the image recognition of the pattern performed by the image recognition unit; and a driving control unit that controls the driving of the vehicle based on the behavior of the surrounding vehicles predicted by the prediction unit.
[0007] (2) In the driving control device of (1), the driving control unit may drive its own vehicle while avoiding the pattern drawn on the road surface by light irradiated from the surrounding vehicles.
[0008] (3) The driving control device of (1) may include a determination unit that determines whether or not the pattern that is the target of image recognition performed by the image recognition unit is a road marking.
[0009] (4) One aspect of the present disclosure is a driving control method comprising: an image recognition step in which a driving control device performs image recognition of a pattern drawn on the road surface by light emitted from surrounding vehicles; a prediction step in which the driving control device predicts the behavior of the surrounding vehicles based on the results of the image recognition of the pattern performed in the image recognition step; and a driving control step in which the driving control device controls the driving of its own vehicle based on the behavior of the surrounding vehicles predicted in the prediction step.
[0010] (5) One aspect of the present disclosure is a program that causes a processor to perform an image recognition step of performing image recognition of a pattern drawn on the road surface by light irradiated from surrounding vehicles; a prediction step of predicting the behavior of the surrounding vehicles based on the results of the image recognition of the pattern performed in the image recognition step; and a driving control step of controlling the driving of the own vehicle based on the behavior of the surrounding vehicles predicted in the prediction step. [Effects of the Invention]
[0011] According to this disclosure, the driving safety of the vehicle can be significantly improved. [Brief explanation of the drawing]
[0012] [Figure 1] This figure shows a first example of the vehicle 1 to which the driving control device 13 of the first embodiment is applied. [Figure 2] This figure shows the first example of a pattern PT drawn on the road surface RS by light emitted from surrounding vehicles SV. [Figure 3] This figure shows a second example of a pattern PT drawn on the road surface RS by light emitted from surrounding vehicles SV. [Figure 4] This is a flowchart illustrating an example of processing performed by the processor 133 of the travel control device 13 of the first embodiment. [Figure 5] This figure shows an example of a vehicle 1 to which the driving control device 13 of the second embodiment is applied. [Figure 6] This is a flowchart illustrating an example of processing performed by the processor 133 of the travel control device 13 of the second embodiment. [Modes for carrying out the invention]
[0013] Hereinafter, embodiments of the driving control device, driving control method, and program of this disclosure will be described with reference to the drawings.
[0014] <First Embodiment> Figure 1 shows a first example of the vehicle 1 to which the driving control device 13 of the first embodiment is applied. In the example shown in Figure 1, the vehicle 1 is equipped with a camera 11, an HMI (Human Machine Interface) 12, a driving control device 13, a steering actuator 14, a braking actuator 15, and a drive actuator 16. Camera 11 captures images of the area around the vehicle 1 (for example, the front, sides, and rear) and transmits the camera images to the driving control device 13. HMI 12 has the function of receiving various operations from the driver of the vehicle 1 and transmits signals indicating the operations of the driver of the vehicle 1 to the driving control device 13.
[0015] In the example shown in Figure 1, the driving control device 13 is configured by, for example, a driver assistance ECU (Electronic Control Unit) (i.e., by a single ECU). In other examples, the driving control device 13 may be composed of, for example, a driver assistance ECU and an image processing ECU (i.e., multiple ECUs).
[0016] In the example shown in Figure 1, the driving control device 13 controls the steering actuator 14, braking actuator 15, and drive actuator 16 based on camera images transmitted from the camera 11, signals indicating the driver's operation of the vehicle 1 transmitted from the HMI 12, etc. The steering actuator 14 has the function of steering the vehicle 1. The steering actuator 14 includes, for example, a power steering system, a steer-by-wire steering system, a rear-wheel steering system, etc. The braking actuator 15 has the function of decelerating the vehicle 1. The braking actuator 15 includes, for example, a hydraulic brake, a regenerative brake, etc. The drive actuator 16 has the function of accelerating the vehicle 1. The drive actuator 16 includes, for example, an engine, an EV (electric vehicle) system, a hybrid system, a fuel cell system, etc.
[0017] The travel control device 13 is composed of a microcomputer including a communication interface (I / F) 131, a memory 132, and a processor 133. The communication interface 131 has an interface circuit for connecting the travel control device 13 to the camera 11, HMI 12, steering actuator 14, braking actuator 15, driving actuator 16, etc. The memory 132 stores programs and various data (such as camera images transmitted from the camera 11, etc.) used in the processes executed by the processor 133. The processor 133 has functions as an acquisition unit 3A, an image recognition unit 3B, a prediction unit 3C, and a travel control unit 3D. The acquisition unit 3A acquires camera images. Further, the acquisition unit 3A acquires signals indicating operations of the driver of the host vehicle 1 received by the HMI 12 (for example, operations for turning on / off driving support functions (such as ACC (Adaptive Cruise Control), FCW (Forward Collision Warning), AEBS (Autonomous Emergency Braking System), emergency steering assist (with active steering function), etc.), steering operations, brake pedal operations, accelerator pedal operations, etc.).
[0018] Based on the camera image acquired by the acquisition unit 3A, the image recognition unit 3B recognizes a pattern PT (refer to FIGS. 2 and 3) drawn on the road surface RS (refer to FIGS. 2 and 3) by the light irradiated from the surrounding vehicle SV (refer to FIGS. 2 and 3).
[0019] FIG. 2 is a diagram showing a first example of the pattern PT drawn on the road surface RS by the light irradiated from the surrounding vehicle SV. In the example shown in FIG. 2, when the surrounding vehicle SV is reversing, it irradiates light to draw a pattern PT indicating that the surrounding vehicle SV is reversing on the road surface RS, to alert pedestrians (not shown), vehicles (not shown), etc. around the surrounding vehicle SV and prevent accidents.
[0020] In the example shown in Figure 1 (the first example of the vehicle 1 to which the driving control device 13 of the first embodiment is applied), the image recognition unit 3B performs image recognition of the pattern PT (a pattern PT indicating that the surrounding vehicle SV is reversing) drawn on the road surface RS by light emitted from the surrounding vehicle SV, as shown in Figure 2, which is drawn on the road surface RS by light emitted from the surrounding vehicle SV when the surrounding vehicle SV is reversing, by training a model obtained by training using training data which is a dataset of training camera images and labels indicating whether or not the pattern contained in the training camera images is a pattern PT indicating that the surrounding vehicle SV is reversing, as shown in Figure 2.
[0021] In the example shown in Figure 1, the prediction unit 3C predicts the behavior of the surrounding vehicle SV based on the results of image recognition of pattern PT performed by the image recognition unit 3B. In detail, in the example shown in Figure 1, when the image recognition unit 3B performs image recognition of a pattern PT indicating that the surrounding vehicle SV will reverse, the prediction unit 3C predicts that the surrounding vehicle SV will reverse as the behavior of the surrounding vehicle SV.
[0022] In the example shown in Figure 1, the driving control unit 3D controls the driving of the vehicle 1 based on the behavior of surrounding vehicles SV predicted by the prediction unit 3C. In detail, in the example shown in Figure 1, when the prediction unit 3C predicts that the surrounding vehicle SV will reverse, the driving control unit 3D drives the vehicle 1 while avoiding the pattern PT (a pattern PT indicating that the surrounding vehicle SV will reverse) drawn on the road surface RS by the light emitted from the surrounding vehicle SV. In other words, the driving control unit 3D drives the vehicle 1 so that the surrounding vehicle SV and the vehicle 1 do not come into contact even if the surrounding vehicle SV reverses. Specifically, for example, when ACC and emergency steering assist are ON, the driving control unit 3D controls the steering actuator 14 and braking actuator 15 so that vehicle 1 drives in a way that avoids pattern PT, which indicates that a surrounding vehicle SV is moving backward, without requiring the driver of vehicle 1 to operate the steering wheel or brake pedal. In another example, when the driver assistance function is ON, the driving control unit 3D may output an alert to the HMI 12 prompting the driver of vehicle 1 to perform steering and brake pedal operations to avoid pattern PT, which indicates that a surrounding vehicle SV is reversing.
[0023] Figure 3 shows a second example of a pattern PT drawn on the road surface RS by light emitted from surrounding vehicles SV. In the example shown in Figure 3, when there is a possibility that the occupant of a surrounding vehicle SV may open the door SVD of the surrounding vehicle SV, the surrounding vehicle SV will emit light to draw a pattern PT on the road surface RS indicating that the door SVD will open, thereby alerting pedestrians (not shown), vehicles (not shown), etc., around the surrounding vehicle SV and attempting to prevent accidents.
[0024] In a second example of the vehicle 1 to which the driving control device 13 of the first embodiment is applied, the image recognition unit 3B performs image recognition of the pattern PT (a pattern PT indicating that the door SVD of a learning surrounding vehicle SV is opened) drawn on the road surface RS by light emitted from the surrounding vehicle SV, as shown in Figure 3, when the occupant of the learning surrounding vehicle SV is likely to open the door SVD of the learning surrounding vehicle SV, by training a model obtained by training using training data which is a dataset of training camera images and labels indicating whether or not the pattern contained in the training camera images is a pattern PT indicating that the door SVD of a learning surrounding vehicle SV is opened, as shown in Figure 3.
[0025] In a second example of the vehicle 1 to which the driving control device 13 of the first embodiment is applied, when the image recognition unit 3B performs image recognition of a pattern PT indicating that the door SVD of a surrounding vehicle SV is open, the prediction unit 3C predicts that the door SVD of the surrounding vehicle SV will open as the behavior of the surrounding vehicle SV.
[0026] In a second example of the vehicle 1 to which the driving control device 13 of the first embodiment is applied, when the prediction unit 3C predicts that the door SVD of a surrounding vehicle SV will open, the driving control unit 3D causes the vehicle 1 to drive while avoiding the pattern PT (a pattern PT indicating that the door SVD of the surrounding vehicle SV will open) drawn on the road surface RS by light emitted from the surrounding vehicle SV. In other words, the driving control unit 3D causes the vehicle 1 to drive so that even if the door SVD of the surrounding vehicle SV opens, the door SVD of the surrounding vehicle SV does not come into contact with the vehicle 1. Specifically, for example, when ACC and emergency steering assist are ON, the driving control unit 3D controls the steering actuator 14 and braking actuator 15 so that vehicle 1 drives while avoiding pattern PT, which indicates that the door SVD of a surrounding vehicle SV is open, without requiring the driver of vehicle 1 to operate the steering wheel or brake pedal. In another example, when the driver assistance function is ON, the driving control unit 3D may output an alert to the HMI 12 prompting the driver of vehicle 1 to perform steering and brake pedal operations to avoid pattern PT, which indicates that the door SVD of a surrounding vehicle SV is open.
[0027] Figure 4 is a flowchart illustrating an example of processing performed by the processor 133 of the travel control device 13 in the first embodiment. In the example shown in Figure 4, in step S10, the image recognition unit 3B performs image recognition of the pattern PT (see Figures 2 and 3) drawn on the road surface RS (see Figures 2 and 3) by light emitted from the surrounding vehicle SV (see Figures 2 and 3), based on the camera image acquired in a step not shown. In step S11, the image recognition unit 3B determines whether the image recognition result performed in step S10 includes a pattern PT drawn on the road surface RS by light emitted from a surrounding vehicle SV. If YES, the process proceeds to step S12; otherwise, the process shown in Figure 4 is terminated. In step S12, the prediction unit 3C predicts the behavior of the surrounding vehicle SV based on the results of the image recognition of the pattern PT performed in step S10. In step S13, the driving control unit 3D controls the driving of the vehicle 1 based on the behavior of the surrounding vehicle SV predicted in step S12.
[0028] In the vehicle 1 to which the driving control device 13 of the first embodiment is applied, the behavior of surrounding vehicles SV is predicted, and the driving of the vehicle 1 is controlled based on the predicted behavior of surrounding vehicles SV. Therefore, the driving safety of the vehicle 1 can be significantly improved compared to when the behavior of surrounding vehicles SV is not predicted.
[0029] <Second Embodiment> The vehicle 1 to which the driving control device 13 of the second embodiment is applied is configured in the same way as the vehicle 1 to which the driving control device 13 of the first embodiment is applied, except for the points described later.
[0030] Figure 5 shows an example of a vehicle 1 to which the driving control device 13 of the second embodiment is applied. In the example shown in Figure 1, the vehicle 1 does not have a LiDAR (Laser Imaging Detection and Ranging) 17 (see Figure 5), but in the example shown in Figure 5, the vehicle 1 is equipped with a LiDAR 17. The LiDAR 17 detects the surrounding conditions of the vehicle 1 and transmits the detection results to the driving control device 13. The acquisition unit 3A acquires the detection results from the LiDAR 17.
[0031] In the example shown in Figure 1, the processor 133 does not function as a determination unit 3E (see Figure 5), but in the example shown in Figure 5, the processor 133 does function as a determination unit 3E. The determination unit 3E determines whether the pattern PT (see Figures 2 and 3) recognized by the image recognition unit 3B is a road marking (e.g., lane markings, road surface markings, etc.). More specifically, if the intensity of the reflected light from the pattern PT received by the light-receiving unit (not shown) of the LiDAR 17 is the same as the intensity of the reflected light from parts of the road surface RS (see Figures 2 and 3) other than the pattern PT, the determination unit 3E determines that the pattern PT recognized by the image recognition unit 3B is not road paint (road markings), but a pattern PT drawn on the road surface RS by light emitted from surrounding vehicles SV. When the intensity of the reflected light from pattern PT received by the light-receiving unit of LiDAR17 differs significantly from the intensity of the reflected light from parts of the road surface RS other than pattern PT, the determination unit 3E determines that the pattern PT recognized by the image recognition unit 3B is road paint (road marking).
[0032] Figure 6 is a flowchart illustrating an example of processing performed by the processor 133 of the travel control device 13 in the second embodiment. In the example shown in Figure 6, in step S20, the image recognition unit 3B performs image recognition of the pattern PT drawn on the road surface RS by light emitted from the surrounding vehicle SV, based on the camera image acquired in a step not shown. In step S21, the image recognition unit 3B determines whether the image recognition result performed in step S20 includes a pattern PT drawn on the road surface RS by light emitted from a surrounding vehicle SV. If YES, the process proceeds to step S22; otherwise, the process shown in Figure 6 is terminated. In step S22, the determination unit 3E determines whether the pattern PT recognized in step S20 is a road marking (e.g., lane markings, road surface markings, etc.). If the answer is NO, the process proceeds to step S23; if the answer is YES, the process shown in Figure 6 is terminated. In step S23, the prediction unit 3C predicts the behavior of the surrounding vehicle SV based on the results of the image recognition of the pattern PT performed in step S20. In step S24, the driving control unit 3D controls the driving of its own vehicle 1 based on the behavior of the surrounding vehicle SV predicted in step S23.
[0033] As described above, in the vehicle 1 to which the driving control device 13 of the second embodiment is applied, if the pattern PT recognized by the image recognition unit 3B is determined by the determination unit 3E to be not a road marking (e.g., lane markings, road surface markings, etc.), the driving control unit 3D executes driving control of the vehicle 1 based on the behavior of surrounding vehicles SV. Therefore, it is possible to suppress the risk that road markings (e.g., lane markings, road surface markings, etc.) may be mistakenly recognized as a pattern PT drawn on the road surface RS by light emitted from surrounding vehicles SV, and that the driving control of the vehicle 1 may be executed inappropriately based on that misrecognition result.
[0034] <Third Embodiment> The vehicle 1 to which the driving control device 13 of the third embodiment is applied is configured in the same way as the vehicle 1 to which the driving control device 13 of the first embodiment is applied, except for the points described later.
[0035] In the example shown in Figure 1 (the first example of the vehicle 1 to which the driving control device 13 of the first embodiment is applied), the processor 133 does not function as a determination unit 3E (see Figure 5). However, in an example of the vehicle 1 to which the driving control device 13 of the third embodiment is applied, the processor 133 does function as a determination unit 3E. The determination unit 3E determines whether the pattern PT (see Figures 2 and 3) recognized by the image recognition unit 3B is a road marking (e.g., lane markings, road surface markings, etc.), similar to the example shown in Figure 5.
[0036] In an example of a vehicle 1 to which the driving control device 13 of the third embodiment is applied, the determination unit 3E, unlike the example shown in Figure 5, determines whether the pattern PT (see Figures 2 and 3) recognized by the image recognition unit 3B is a road marking (e.g., lane markings, road markings, etc.) by using a machine learning model. Specifically, the determination unit 3E determines whether the pattern PT recognized by the image recognition unit 3B is a road marking by using a machine learning model obtained by training with training data, which is a dataset of training camera images and labels indicating whether the pattern contained in the training camera images is a pattern PT drawn on the road surface RS by light irradiated from a training surrounding vehicle SV, or a road paint (road marking). In an example of a vehicle 1 to which the driving control device 13 of the third embodiment is applied, when the determination unit 3E determines that the pattern PT recognized by the image recognition unit 3B is not a road marking, the prediction unit 3C predicts the behavior of surrounding vehicles SV, and the driving control unit 3D controls the driving of the vehicle 1.
[0037] <Fourth Embodiment> The vehicle 1 to which the driving control device 13 of the fourth embodiment is applied is configured in the same way as the vehicle 1 to which the driving control device 13 of the third embodiment is applied, except for the points described later.
[0038] In an example of a vehicle 1 to which the driving control device 13 of the third embodiment is applied, as described above, the determination unit 3E uses a machine learning model to determine whether the pattern PT (see Figures 2 and 3) recognized by the image recognition unit 3B is a road marking (e.g., lane markings, road surface markings, etc.). On the other hand, in an example of the vehicle 1 to which the driving control device 13 of the fourth embodiment is applied, the determination unit 3E determines whether the pattern PT recognized by the image recognition unit 3B is a road marking based on whether or not there is a time change in the relative positional relationship between the pattern PT recognized by the image recognition unit 3B and the surrounding vehicle SV. If there is a time change in the relative positional relationship between the pattern PT recognized by the image recognition unit 3B and the surrounding vehicle SV (more specifically, if the position of the pattern PT has not changed but the position of the surrounding vehicle SV has changed), the determination unit 3E determines that the pattern PT recognized by the image recognition unit 3B is a road marking.
[0039] <Fifth Embodiment> A vehicle 1 to which the driving control device 13 of the fifth embodiment is applied is configured in the same way as a vehicle 1 to which any of the driving control devices 13 of the first to fourth embodiments described above is applied, except for the points described later.
[0040] As described above, in the vehicle 1 to which any of the first to fourth embodiments of the driving control device 13 is applied, the driving control device 13 is configured, for example, by a driver assistance ECU. On the other hand, in the vehicle 1 to which the driving control device 13 of the fifth embodiment is applied, the driving control device 13 is configured, for example, by an automatic driving ECU. The driving control device 13 controls the steering actuator 14, the braking actuator 15, and the drive actuator 16 based on camera images transmitted from the camera 11, signals transmitted from the HMI 12 indicating an operation by the driver of the vehicle 1 to put the vehicle 1 into automatic driving mode, etc.
[0041] In the vehicle 1 to which the driving control device 13 of the fifth embodiment is applied, the acquisition unit 3A acquires signals indicating the driver's operation of the vehicle 1 received by the HMI 12 (for example, an operation to put the vehicle 1 into automatic driving mode, an operation to deactivate the automatic driving mode of the vehicle 1, etc.).
[0042] In an example of a vehicle 1 to which the driving control device 13 of the fifth embodiment is applied, when the prediction unit 3C predicts that the surrounding vehicle SV will move backward, the driving control unit 3D generates a driving plan to drive the vehicle 1 while avoiding the pattern PT (a pattern PT indicating that the surrounding vehicle SV will move backward) drawn on the road surface RS by light emitted from the surrounding vehicle SV, and controls the steering actuator 14 and the braking actuator 15 based on that driving plan. In another example to which the driving control device 13 of the fifth embodiment is applied to the vehicle 1, when the prediction unit 3C predicts that the door SVD of a surrounding vehicle SV will open as a behavior of the surrounding vehicle SV, the driving control unit 3D generates a driving plan to drive the vehicle 1 while avoiding the pattern PT (a pattern PT indicating that the door SVD of the surrounding vehicle SV will open) drawn on the road surface RS by light emitted from the surrounding vehicle SV, and controls the steering actuator 14 and the braking actuator 15 based on that driving plan.
[0043] As described above, embodiments of the driving control device, driving control method, and program of this disclosure have been explained with reference to the drawings. However, the driving control device, driving control method, and program of this disclosure are not limited to the embodiments described above, and can be modified as appropriate without departing from the spirit of this disclosure. The configurations of each example of the embodiments described above may be combined as appropriate. In each example of the embodiments described above, the processing performed in the driving control device 13 (e.g., driver assistance ECU, autonomous driving ECU, etc.) was described as software processing performed by executing a program. However, the processing performed in the driving control device 13 may be hardware processing. Alternatively, the processing performed in the driving control device 13 may be a combination of software and hardware processing. Furthermore, the program stored in the memory 132 of the driving control device 13 (a program that realizes the functions of the processor 133 of the driving control device 13) may be recorded on a computer-readable storage medium such as a semiconductor memory, magnetic recording medium, optical recording medium, etc., and provided and distributed. [Explanation of Symbols]
[0044] 1...Vehicle, 11...Camera, 12...HMI, 13...Driving control device, 131...Communication interface, 132...Memory, 133...Processor, 3A...Acquisition unit, 3B...Image recognition unit, 3C...Prediction unit, 3D...Driving control unit, 3E...Determination unit, 14...Steering actuator, 15...Brake actuator, 16...Drive actuator, 17...LiDAR, SV...Surrounding vehicles, SVD...Door, RS...Road surface, PT...Pattern
Claims
1. An image recognition unit that performs image recognition of patterns drawn on the road surface by light emitted from surrounding vehicles, A prediction unit predicts the behavior of the surrounding vehicles based on the results of image recognition of the pattern performed by the image recognition unit, The vehicle comprises a driving control unit that controls the driving of the vehicle based on the behavior of the surrounding vehicles predicted by the prediction unit, The image recognition unit performs image recognition of the pattern indicating that the door of the surrounding vehicle is open. The prediction unit predicts that the doors of the surrounding vehicles will open as part of the behavior of the surrounding vehicles. The aforementioned driving control unit causes the vehicle to drive while avoiding the pattern indicating that the doors of the surrounding vehicles are open, which is drawn on the road surface by light emitted from the surrounding vehicles.
2. The driving control device according to claim 1, further comprising a determination unit that determines whether or not the pattern that is the target of image recognition performed by the image recognition unit is a road marking.
3. A driving control device performs an image recognition step of performing image recognition of a pattern drawn on the road surface by light irradiated from surrounding vehicles, The driving control device includes a prediction step in which it predicts the behavior of the surrounding vehicles based on the results of the image recognition of the pattern performed in the image recognition step, The driving control device comprises a driving control step which controls the driving of its own vehicle based on the behavior of the surrounding vehicles predicted in the prediction step, In the image recognition step, image recognition of the pattern indicating that the door of the surrounding vehicle is open is performed. In the prediction step, it is predicted that the doors of the surrounding vehicles will open as part of the behavior of the surrounding vehicles. A driving control method in which, in the driving control step, the vehicle is made to drive while avoiding the pattern indicating that the doors of the surrounding vehicles are open, which is drawn on the road surface by light emitted from the surrounding vehicles.
4. The processor includes: An image recognition step that performs image recognition of a pattern drawn on the road surface by light emitted from surrounding vehicles, A prediction step in which the behavior of the surrounding vehicles is predicted based on the results of the image recognition of the pattern performed in the image recognition step, A program for executing a driving control step which controls the driving of the vehicle based on the predicted behavior of the surrounding vehicles in the prediction step, In the image recognition step, image recognition of the pattern indicating that the door of the surrounding vehicle is open is performed. In the prediction step, it is predicted that the doors of the surrounding vehicles will open as part of the behavior of the surrounding vehicles. The program, in the aforementioned driving control step, causes the vehicle to drive while avoiding the pattern indicating that the doors of the surrounding vehicles are open, which is drawn on the road surface by light emitted from the surrounding vehicles.