Surrounding situation recognition device, surrounding situation recognition method, and program

Abstract

To appropriately determine the presence / absence of an object which is likely to fall onto the vicinity of a host vehicle from surrounding vehicles.SOLUTION: A surrounding situation recognition device 16 comprises: a first determination unit 3C for determining whether or not an object mounted on a surrounding vehicle located in the vicinity of a host vehicle 1 corresponds to a specific object which is an object where the number of cases processed in the past as a falling object on a road is greater than or equal to a threshold value; and a second determination unit 3D for determining the presence / absence of an object which is likely to fall from the surrounding vehicle to the vicinity of the host vehicle 1 based on a determination result of the first determination unit 3C.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a surrounding situation recognition device, a surrounding situation recognition method, and a program. [Background technology]

[0002] Patent Document 1 describes a technology that detects signs that cargo loaded on the loading platform of a leading vehicle is about to fall and issues a warning that the cargo is about to fall. In other words, the technology described in Patent Document 1 requires that signs that cargo loaded on the loading platform of a leading vehicle is about to fall be detected in order to issue a warning that the cargo is about to fall. In the technology described in Patent Document 1, to detect signs that cargo is about to fall, images of the cargo are continuously taken at predetermined intervals, an image taken at a certain point in time is compared with an image taken thereafter, changes in the appearance of the cargo are continuously monitored, and it is determined whether the cargo will fall or not based on the amount of change in the appearance of the cargo. In other words, the technology described in Patent Document 1 requires image processing with a heavy computational load to detect signs that cargo loaded on the loading platform of a leading vehicle is about to fall. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-002410 Summary of the Invention [Problem to be solved by the invention]

[0004] On the other hand, statistics on the number of incidents that have been treated as falling objects on roads in the past are compiled by the Ministry of Land, Infrastructure, Transport and Tourism, highway companies, etc., so there is a need for technology that can use such statistics to determine whether there are any objects that are likely to fall around the vehicle without having to perform image processing that requires a large computational load. Driving assistance devices such as that described in Patent Document 1 have been proposed in the past, but the previously proposed technologies are unable to properly determine whether or not there is an object that is likely to fall from a nearby vehicle into the vicinity of the vehicle.

[0005] In view of the above, the present disclosure aims to provide a surrounding situation recognition device, a surrounding situation recognition method, and a program that can appropriately determine whether or not an object is likely to fall from a nearby vehicle into the vicinity of the vehicle. is. [Means for solving the problem]

[0006] (1) One aspect of the present disclosure is a surrounding situation recognition device that includes a first determination unit that determines whether an object carried by a nearby vehicle located in the vicinity of the host vehicle corresponds to a specific object, which is an object that has been previously processed as a fallen object on a road a threshold number of times or more, and a second determination unit that determines whether there is an object that is likely to fall from the nearby vehicle into the vicinity of the host vehicle based on the determination result of the first determination unit.

[0007] (2) In the surrounding situation recognition device of (1), the first determination unit may determine whether the object mounted on the surrounding vehicle corresponds to the specific object, which is an object that has been previously processed as a fallen object on the road on which the vehicle and the surrounding vehicle are currently traveling a threshold or more in number.

[0008] (3) The surrounding situation recognition device of (1) or (2) may include a third determination unit that determines whether an object mounted on the surrounding vehicle is mounted on the surrounding vehicle in a state that could cause it to fall, and the second determination unit may determine that there is an object that is likely to fall from the surrounding vehicle into the vicinity of the vehicle when the first determination unit determines that the object mounted on the surrounding vehicle corresponds to the specific object and when the third determination unit determines that the object mounted on the surrounding vehicle is mounted on the surrounding vehicle in a state that could cause it to fall.

[0009] (4) One aspect of the present disclosure is a surrounding situation recognition method including a first determination step in which a surrounding situation recognition device determines whether an object mounted on a nearby vehicle located in the vicinity of the host vehicle corresponds to a specific object that has been previously processed as a fallen object on the road a threshold or more times, and a second determination step in which the surrounding situation recognition device determines whether there is an object that is likely to fall from the nearby vehicle into the vicinity of the host vehicle based on the determination result in the first determination step.

[0010] (5) One aspect of the present disclosure is a program for causing a processor to execute a first determination step of determining whether an object carried by a nearby vehicle located in the vicinity of the host vehicle corresponds to a specific object, which is an object that has been previously processed as a fallen object on the road a threshold number of times or more, and a second determination step of determining whether or not an object is likely to fall from the nearby vehicle into the vicinity of the host vehicle based on the determination result of the first determination step. [Effects of the Invention]

[0011] According to the present disclosure, it is possible to appropriately determine whether or not an object is likely to fall from a nearby vehicle into the vicinity of the host vehicle. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a diagram showing an example of a host vehicle 1 to which a surrounding situation recognition device 16 according to a first embodiment is applied. [Figure 2] 5 is a flowchart illustrating an example of processing executed by a processor 163 of the surrounding situation recognition device 16 according to the first embodiment. [Figure 3] 10 is a flowchart illustrating an example of processing executed by a processor 163 of a surrounding situation recognition device 16 according to a third embodiment. [Figure 4] FIG. 10 is a diagram showing an example of a host vehicle 1 to which a surrounding situation recognition device 16 according to a fourth embodiment is applied. [Figure 5]10 is a flowchart illustrating an example of processing executed by a processor 163 of a surrounding situation recognition device 16 according to a fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, embodiments of a surrounding situation recognition device, a surrounding situation recognition method, and a program according to the present disclosure will be described with reference to the drawings.

[0014] First Embodiment FIG. 1 is a diagram showing an example of a host vehicle 1 to which a surrounding situation recognition device 16 according to the first embodiment is applied. In the example shown in Figure 1, the vehicle 1 is equipped with a surrounding situation sensor 11, a vehicle state sensor 12, an HMI (Human Machine Interface) 13, a communication device 14, a vehicle control device 15, a steering actuator 15A, a braking actuator 15B, a driving actuator 15C, and a surrounding situation recognition device 16. The surrounding situation sensor 11 measures the surrounding situation of the host vehicle 1 (for example, surrounding vehicles located around the host vehicle 1, objects mounted on the surrounding vehicles, obstacles located around the host vehicle 1, etc.), and transmits the measurement results of the surrounding situation of the host vehicle 1 to the vehicle control device 15 and the surrounding situation recognition device 16. The surrounding situation sensor 11 includes, for example, a camera, LiDAR (Light Detection And Ranging), etc.

[0015] The vehicle state sensor 12 measures the state of the host vehicle 1 and transmits the measurement results of the state of the host vehicle 1 to the vehicle control device 15. The vehicle state sensor 12 includes, for example, a vehicle speed sensor, an acceleration sensor, a yaw rate sensor, a gyro sensor, and the like. The HMI 13 has a function of accepting various operations by the driver of the vehicle 1 and transmits a signal indicating the operation by the driver of the vehicle 1 to the vehicle control device 15. The communication device 14 communicates with the outside of the vehicle 1 and transmits the results of communication with the outside of the vehicle 1 to the surrounding situation recognition device 16. The vehicle control device 15 controls the steering actuator 15A, the braking actuator 15B, and the drive actuator 15C based on information (data, signals) transmitted from the surroundings sensor 11, the vehicle state sensor 12, and the HMI 13, for example.

[0016] The surrounding situation recognition device 16 is configured by a microcomputer equipped with a communication interface (I / F) 161, a memory 162, and a processor 163. The communication interface 161 has an interface circuit for connecting the surrounding situation recognition device 16 to the surrounding situation sensor 11, the vehicle state sensor 12, the HMI 13, the communication device 14, and the vehicle control device 15. The memory 162 stores programs and various data used in the processing executed by the processor 163. In detail, the memory 162 stores information about specific objects acquired by the communication device 14 from outside the vehicle 1 (for example, a website showing information about specific objects). A specific object is an object that has been processed as a fallen object on the road more than a threshold number of times in the past. The information about specific objects is, for example, ranking information about fallen objects. In the example shown in Figure 1, information about the specific object is obtained from outside the vehicle 1 by the communication device 14 and stored in memory 162, but in other examples, information about the specific object may be stored in memory 162, for example, when the vehicle 1 is manufactured (in other words, information about the specific object does not have to be obtained from outside the vehicle 1 by the communication device 14).

[0017] In the example shown in FIG. 1, the processor 163 has a function as an acquisition unit 3A, a function as a recognition unit 3B, a function as a first judgment unit 3C, a function as a second judgment unit 3D, and a function as a processing unit 3E. The acquisition unit 3A acquires the measurement results of the surrounding situation sensor 11 from the surrounding situation sensor 11. The measurement results of the surrounding situation sensor 11 include, for example, an image including surrounding vehicles and objects mounted on the surrounding vehicles captured by a camera serving as the surrounding situation sensor 11, and measurement results (e.g., three-dimensional images) of the surrounding vehicles and objects mounted on the surrounding vehicles captured by a LiDAR serving as the surrounding situation sensor 11. The acquisition unit 3A also acquires information related to the specific object from the memory 162.

[0018] The recognition unit 3B recognizes objects mounted on peripheral vehicles located around the host vehicle 1 based on the measurement results of the surrounding condition sensor 11 acquired by the acquisition unit 3A. In detail, the recognition unit 3B recognizes objects mounted on peripheral vehicles located around the host vehicle 1 based on the measurement results of the surrounding condition sensor 11 by using a model obtained by performing learning using teacher data, which is a data set of measurement results of the surrounding condition sensor mounted on the training vehicle and labels indicating attributes of objects (training objects) mounted on peripheral vehicles (training peripheral vehicles) located around the training vehicle that are the measurement targets of the surrounding condition sensor.

[0019] The first determination unit 3C determines whether or not the object mounted on the nearby vehicle recognized by the recognition unit 3B corresponds to a specific object (an object that has been processed as fallen objects on the road a threshold or more in the past). In detail, the first determination unit 3C determines whether or not the object mounted on the nearby vehicle corresponds to a specific object based on information about the specific object stored in the memory 162 (for example, ranking information about objects that have been processed as fallen objects on the road a threshold or more in the past). Based on the determination result of the first determination unit 3C, the second determination unit 3D determines whether or not there is an object that is likely to fall from a nearby vehicle into the vicinity of the host vehicle 1. In particular, if the first determination unit 3C determines that an object carried by the nearby vehicle corresponds to a specific object (an object that has been processed as a fallen object on the road a threshold or more in the past), the second determination unit 3D determines that there is an object that is likely to fall from a nearby vehicle into the vicinity of the host vehicle 1. On the other hand, if the first determination unit 3C determines that the object carried by the nearby vehicle does not correspond to a specific object, the second determination unit 3D determines that there is no object that is likely to fall from a nearby vehicle into the vicinity of the host vehicle 1.

[0020] When the second judgment unit 3D judges that there is an object that is likely to fall from a nearby vehicle onto the periphery of the host vehicle 1, the processing unit 3E executes control to output a warning to the HMI 13 indicating that there is an object that is likely to fall from a nearby vehicle onto the periphery of the host vehicle 1. Therefore, in the example shown in Fig. 1, even if the object falls from a nearby vehicle into the vicinity of the host vehicle 1, it is possible to reduce the risk of a collision or the like between the object and the host vehicle 1. In detail, in the example shown in Fig. 1, by utilizing information about the specific object, it is possible to appropriately determine whether or not an object is likely to fall from a nearby vehicle into the vicinity of the host vehicle 1, without performing image processing that involves a large computational load.

[0021] FIG. 2 is a flowchart illustrating an example of processing executed by the processor 163 of the surrounding situation recognition device 16 according to the first embodiment. 2, in step S10, the acquisition unit 3A acquires the measurement result of the surrounding situation sensor 11 from the surrounding situation sensor 11. The acquisition unit 3A also acquires information about the specific object from the memory 162. In step S11, the recognition unit 3B recognizes objects mounted on surrounding vehicles located around the host vehicle 1 based on the measurement results of the surrounding situation sensor 11 acquired in step S10. In step S12, the first determination unit 3C determines whether the object carried by the nearby vehicle recognized in step S11 corresponds to a specific object (an object that has been processed as a fallen object on the road more than a threshold value in the past) based on the information about the specific object acquired in step S10. If the result is YES, the process proceeds to step S13, and if the result is NO, the process proceeds to step S15.

[0022] In step S13, the second determination unit 3D determines that there is an object that is likely to fall from the surrounding vehicle onto the periphery of the host vehicle 1. In step S14, the processing unit 3E executes control to cause the HMI 13 to output a warning indicating that there is an object that is likely to fall from a nearby vehicle onto the periphery of the host vehicle 1. In step S15, the second determination unit 3D determines that there is no object that is likely to fall into the vicinity of the host vehicle 1 from the nearby vehicles.

[0023] Second Embodiment The host vehicle 1 to which the surrounding situation recognition device 16 of the second embodiment is applied is configured in the same manner as the host vehicle 1 to which the surrounding situation recognition device 16 of the first embodiment described above is applied, except for the points described below.

[0024] In the example shown in Figure 1 (an example of a host vehicle 1 to which the surrounding situation recognition device 16 of the first embodiment is applied), the vehicle control device 15 does not have an automatic driving function that controls the steering actuator 15A, braking actuator 15B, and drive actuator 15C to cause the host vehicle 1 to travel autonomously without the need for operation by the driver of the host vehicle 1. On the other hand, in an example of the host vehicle 1 to which the surrounding situation recognition device 16 of the second embodiment is applied, the vehicle control device 15 has an automatic driving function that controls the steering actuator 15A, the braking actuator 15B, and the drive actuator 15C to cause the host vehicle 1 to travel autonomously without the need for operation by the driver of the host vehicle 1. Specifically, the vehicle control device 15 generates a travel plan for the host vehicle 1 to reach a destination based on, for example, map information, position information of the host vehicle 1, information indicating the destination of the host vehicle 1, etc. Furthermore, the vehicle control device 15 causes the host vehicle 1 to travel autonomously in accordance with the travel plan. In detail, the vehicle control device 15 causes the host vehicle 1 to travel autonomously while modifying the travel plan based on, for example, measurement results of the surrounding situation sensor 11 so as to avoid collisions between the host vehicle 1 and surrounding vehicles, etc.

[0025] In the example shown in Figure 1 (an example of the host vehicle 1 to which the surrounding situation recognition device 16 of the first embodiment is applied), as described above, when the second judgment unit 3D determines that there is an object that is likely to fall from a nearby vehicle into the vicinity of the host vehicle 1, the processing unit 3E executes control to cause the HMI 13 to output a warning indicating that there is an object that is likely to fall from a nearby vehicle into the vicinity of the host vehicle 1. On the other hand, in an example of the host vehicle 1 to which the surrounding situation recognition device 16 of the second embodiment is applied, when the second determination unit 3D determines that there is an object that is likely to fall from a nearby vehicle into the vicinity of the host vehicle 1, the processing unit 3E causes the vehicle control device 15 to modify the driving plan so that the host vehicle 1 can travel safely without a collision between the object and the host vehicle 1 even if the object falls from a nearby vehicle into the vicinity of the host vehicle 1. The vehicle control device 15 modifies the driving plan in response to an instruction from the processing unit 3E, and causes the host vehicle 1 to travel autonomously in accordance with the modified driving plan. Therefore, in an example of the host vehicle 1 to which the surrounding situation recognition device 16 of the second embodiment is applied, even if the object falls from a nearby vehicle into the vicinity of the host vehicle 1, it is possible to reduce the risk of a collision or the like between the object and the host vehicle 1. In detail, by utilizing information about the specific object without performing image processing that involves a large computational load, it is possible to appropriately determine whether or not there is an object that is likely to fall into the vicinity of the host vehicle 1 from a nearby vehicle.

[0026] <Third embodiment> The host vehicle 1 to which the surrounding situation recognition device 16 of the third embodiment is applied is configured in the same manner as the host vehicle 1 to which the surrounding situation recognition device 16 of the first embodiment described above is applied, except for the points described below.

[0027] In the example shown in Figure 1 (an example of the host vehicle 1 to which the surrounding situation recognition device 16 of the first embodiment is applied), as described above, the recognition unit 3B recognizes objects mounted on surrounding vehicles located around the host vehicle 1 based on the measurement results of the surrounding situation sensor 11 acquired by the acquisition unit 3A, but does not recognize the road on which the host vehicle 1 and the surrounding vehicles are currently traveling. On the other hand, in an example of a host vehicle 1 to which the surrounding situation recognition device 16 of the third embodiment is applied, the recognition unit 3B recognizes objects mounted on surrounding vehicles located around the host vehicle 1 based on the measurement results of the surrounding situation sensor 11 acquired by the acquisition unit 3A, and also recognizes the road on which the host vehicle 1 and surrounding vehicles are currently traveling based on the measurement results of the surrounding situation sensor 11 acquired by the acquisition unit 3A. In other words, in an example of a host vehicle 1 to which the surrounding situation recognition device 16 of the third embodiment is applied, the measurement results of the surrounding situation sensor 11 include, for example, an image including the road on which the host vehicle 1 and surrounding vehicles are currently traveling, captured by a camera serving as the surrounding situation sensor 11, and measurement results (for example, a three-dimensional image) of the road on which the host vehicle 1 and surrounding vehicles are currently traveling, captured by a LiDAR serving as the surrounding situation sensor 11.

[0028] In one example of a host vehicle 1 to which the surrounding situation recognition device 16 of the third embodiment is applied, the recognition unit 3B uses a model obtained by learning using teacher data, which is a data set of measurement results from a surrounding situation sensor mounted on a training vehicle, and labels included in the measurement results of the surrounding situation sensor indicating the roads on which the training vehicle and surrounding vehicles (training surrounding vehicles) located around it are traveling, to recognize the road (e.g., Expressway A, Expressway B, etc.) on which the host vehicle 1 and surrounding vehicles are currently traveling, based on the measurement results of the surrounding situation sensor 11. In another example of the host vehicle 1 to which the surrounding situation recognition device 16 of the third embodiment is applied, the acquisition unit 3A may acquire GPS (Global Positioning System) signals and map information used to recognize the road on which the host vehicle 1 and the surrounding vehicles are currently traveling. That is, in this example, the recognition unit 3B recognizes the road on which the host vehicle 1 and the surrounding vehicles are currently traveling, based on the GPS signals and map information acquired by the acquisition unit 3A.

[0029] In an example of a host vehicle 1 to which the surrounding situation recognition device 16 of the third embodiment is applied, the first judgment unit 3C judges whether an object mounted on a nearby vehicle corresponds to a specific object, which is an object that has been previously processed as a fallen object on the road on which the host vehicle 1 and the nearby vehicles are currently traveling a threshold or more in number. In detail, the first judgment unit 3C judges whether an object carried on a nearby vehicle corresponds to a specific object that has been previously processed as a fallen object a threshold number of times or more on the road on which the vehicle 1 and the nearby vehicles are currently traveling, based on ranking information of objects that have been previously processed as a fallen object a threshold number of times or more on the road on which the vehicle 1 and the nearby vehicles are currently traveling (e.g., highway A) among information about the specific object stored in memory 162 (e.g., ranking information of objects that have previously been processed as a fallen object a threshold number of times or more, ranking information of objects that have previously been processed as a fallen object a threshold number of times or more, etc.).

[0030] FIG. 3 is a flowchart illustrating an example of processing executed by the processor 163 of the surrounding situation recognition device 16 according to the third embodiment. 3, in step S20, the acquisition unit 3A acquires the measurement result of the surrounding situation sensor 11 from the surrounding situation sensor 11. The acquisition unit 3A also acquires information about the specific object from the memory 162. In step S21, based on the measurement results of the surrounding condition sensor 11 acquired in step S20, the recognition unit 3B recognizes objects mounted on surrounding vehicles located around the host vehicle 1. Furthermore, based on the measurement results of the surrounding condition sensor 11 acquired in step S20, the recognition unit 3B recognizes the road on which the host vehicle 1 and surrounding vehicles are currently traveling. In step S22, the first determination unit 3C determines, based on the information about the specific object acquired in step S20, whether the object carried by the nearby vehicle recognized in step S21 corresponds to a specific object that has been processed as a fallen object on the road on which the host vehicle 1 and the nearby vehicles are currently traveling a number of times equal to or greater than a threshold value. If the answer is YES, the process proceeds to step S23, and if the answer is NO, the process proceeds to step S25.

[0031] In step S23, the second determination unit 3D determines that there is an object that is likely to fall from the surrounding vehicle onto the periphery of the host vehicle 1. In step S24, the processing unit 3E executes control to cause the HMI 13 to output a warning indicating that there is an object that is likely to fall from a nearby vehicle onto the periphery of the host vehicle 1. In step S25, the second determination unit 3D determines that there is no object that is likely to fall into the vicinity of the host vehicle 1 from the nearby vehicles.

[0032] <Fourth embodiment> The host vehicle 1 to which the surrounding situation recognition device 16 of the fourth embodiment is applied is configured in the same manner as the host vehicle 1 to which the surrounding situation recognition device 16 of the first embodiment described above is applied, except for the points described below.

[0033] FIG. 4 is a diagram showing an example of a host vehicle 1 to which a surrounding situation recognition device 16 according to the fourth embodiment is applied. In the example shown in FIG. 4, the processor 163 has a function as an acquisition unit 3A, a function as a recognition unit 3B, a function as a first judgment unit 3C, a function as a second judgment unit 3D, a function as a third judgment unit 3F, and a function as a processing unit 3E. The third determination unit 3F determines whether or not an object mounted on a nearby vehicle is mounted on the nearby vehicle in a state that could cause it to fall. For example, if the object carried on the nearby vehicle is in an overloaded state, the third determination unit 3F determines that the object carried on the nearby vehicle is in a state that could cause it to fall. In detail, the third determination unit 3F determines whether the object carried on the nearby vehicle is in an overloaded state based on the measurement results of the surrounding situation sensor 11 by using a model obtained by learning using teacher data, which is a data set of measurement results of a surrounding situation sensor carried on the learning vehicle and labels indicating whether an object (learning object) carried on a nearby vehicle (learning surrounding vehicle) located around the learning vehicle that is the measurement target of the surrounding situation sensor is in an overloaded state. In another example, when an object mounted on a nearby vehicle is protruding from the surrounding vehicle, the third judgment unit 3F may determine that the object mounted on the nearby vehicle is mounted on the nearby vehicle in a state that could become a falling object. In yet another example, when an object mounted on a nearby vehicle is mounted on the nearby vehicle without being fixed to the nearby vehicle, the third judgment unit 3F may determine that the object mounted on the nearby vehicle is mounted on the nearby vehicle in a state that could become a falling object.

[0034] In the example shown in Figure 4, if the first judgment unit 3C judges that an object carried on a nearby vehicle corresponds to a specific object (an object that has been treated as a fallen object on the road more than a threshold number of times in the past), and if the third judgment unit 3F judges that the object carried on a nearby vehicle is carried on the nearby vehicle in a state that could become a fallen object, the second judgment unit 3D judges that there is an object that is likely to fall from the nearby vehicle into the vicinity of the vehicle. On the other hand, if the first judgment unit 3C determines that the object carried on the surrounding vehicle does not correspond to a specific object, the second judgment unit 3D determines that there is no object that is likely to fall from the surrounding vehicle into the vicinity of the vehicle 1. In addition, even if the third judgment unit 3F judges that an object carried on a nearby vehicle is not in a state that could become a falling object, the second judgment unit 3D judges that there is no object that is likely to fall from the nearby vehicle into the vicinity of the vehicle 1.

[0035] FIG. 5 is a flowchart illustrating an example of processing executed by the processor 163 of the surrounding situation recognition device 16 according to the fourth embodiment. 5, in step S30, the acquisition unit 3A acquires the measurement result of the surrounding situation sensor 11 from the surrounding situation sensor 11. The acquisition unit 3A also acquires information about the specific object from the memory 162. In step S31, the recognition unit 3B recognizes objects mounted on surrounding vehicles located around the host vehicle 1 based on the measurement results of the surrounding situation sensor 11 acquired in step S30. In step S32, the first determination unit 3C determines whether the object carried by the nearby vehicle recognized in step S31 corresponds to a specific object (an object that has been processed as a fallen object on the road more than a threshold value in the past) based on the information about the specific object acquired in step S30. If the result is YES, the process proceeds to step S33, and if the result is NO, the process proceeds to step S36.

[0036] In step S33, the third determination unit 3F determines whether the object carried on the nearby vehicle is in a state that could cause it to fall. If the determination is YES, the process proceeds to step S34, and if the determination is NO, the process proceeds to step S36. In step S34, the second determination unit 3D determines that there is an object that is likely to fall from the surrounding vehicle onto the periphery of the host vehicle 1. In step S35, the processing unit 3E executes control to cause the HMI 13 to output a warning indicating that there is an object that is likely to fall from a nearby vehicle onto the periphery of the host vehicle 1. In step S36, the second determination unit 3D determines that there is no object that is likely to fall into the vicinity of the host vehicle 1 from the nearby vehicles.

[0037] As described above, the embodiments of the peripheral situation recognition device, the peripheral situation recognition method, and the program of the present disclosure have been described with reference to the drawings. However, the peripheral situation recognition device, the peripheral situation recognition method, and the program of the present disclosure are not limited to the above-described embodiments, and appropriate modifications may be made without departing from the spirit of the present disclosure. The configurations of the above-described embodiments may be combined as appropriate. In the above-described embodiments, the processing performed by the peripheral situation recognition device 16 has been described as software processing performed by executing a program. However, the processing performed by the peripheral situation recognition device 16 may be processing performed by hardware. Alternatively, the processing performed by the peripheral situation recognition device 16 may be processing that combines both software and hardware. Furthermore, the program stored in the memory 162 of the peripheral situation recognition device 16 (the program that realizes the functions of the processor 163 of the peripheral situation recognition device 16) may be recorded on a computer-readable storage medium such as a semiconductor memory, a magnetic recording medium, an optical recording medium, etc., and provided, distributed, etc. [Explanation of symbols]

[0038] 1...Own vehicle, 11...Surrounding condition sensor, 12...Vehicle condition sensor, 13...HMI, 14...Communication device, 15...Vehicle control device, 15A...Steering actuator, 15B...Braking actuator, 15C...Driving actuator, 16...Surrounding condition recognition device, 161...Communication interface, 162...Memory, 163...Processor, 3A...Acquisition unit, 3B...Recognition unit, 3C...First judgment unit, 3D...Second judgment unit, 3E...Processing unit, 3F...Third judgment unit

Claims

1. a first determination unit that determines whether an object carried by a nearby vehicle located in the vicinity of the vehicle corresponds to a specific object that has been processed as a fallen object on a road a threshold or more in the past; a second determination unit that determines whether or not there is an object that is likely to fall from the nearby vehicle into the vicinity of the host vehicle based on the determination result of the first determination unit.

2. 2. The surrounding situation recognition device according to claim 1, wherein the first determination unit determines whether the object mounted on the nearby vehicle corresponds to the specific object, which is an object that has been previously processed as a fallen object on a road on which the host vehicle and the nearby vehicle are currently traveling a number of times greater than a threshold.

3. a third determination unit that determines whether or not an object mounted on the nearby vehicle is mounted on the nearby vehicle in a state that could cause it to fall; 2. The surrounding situation recognition device according to claim 1, wherein the second determination unit determines that there is an object that is likely to fall from the surrounding vehicle into the vicinity of the host vehicle when the first determination unit determines that an object mounted on the surrounding vehicle corresponds to the specific object and when the third determination unit determines that the object mounted on the surrounding vehicle is mounted on the surrounding vehicle in a state that could cause it to fall.

4. a first determination step in which the surrounding situation recognition device determines whether an object mounted on a nearby vehicle located around the host vehicle corresponds to a specific object that has been processed as a fallen object on a road a threshold or more in the past; a second determination step in which the surrounding situation recognition device determines, based on the determination result in the first determination step, whether or not there is an object that is likely to fall from the nearby vehicle into the vicinity of the host vehicle.

5. The processor a first determination step of determining whether an object carried by a nearby vehicle located in the vicinity of the vehicle corresponds to a specific object that has been processed as a fallen object on a road a number of times in the past that is equal to or exceeds a threshold value; and a second determination step of determining whether or not there is an object that is likely to fall from the nearby vehicle into the vicinity of the host vehicle, based on the determination result in the first determination step.

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