Ambience determining device

Abstract

The present application relates to a kind of peripheral environment determination device.The peripheral environment determination device has: camera and peripheral environment detection unit, is configured to detect the environmental condition of the periphery of the vehicle;Camera, target detection unit and other vehicle determination unit, are configured to detect whether there is other vehicle beyond the vehicle or with the vehicle of the vehicle;And severe environment determination unit, is configured to determine whether the peripheral environment of the vehicle is severe environment based on the environmental condition of the periphery of the vehicle and the presence or absence of other vehicle.The severe environment determination unit is configured to compare the detection score of the environmental condition of the periphery of the vehicle with the severe environment threshold corresponding to the environmental condition of the periphery of the vehicle, and determine whether the peripheral environment of the vehicle is severe environment.

Description

Technical Field

[0001] This disclosure relates to a device for determining the surrounding environment. Background Technology

[0002] As a device for determining the surrounding environment, the technology described in Japanese Patent Application Publication No. 2022-14729 is known, for example. The surrounding environment determination device described in Japanese Patent Application Publication No. 2022-14729 analyzes images captured by a camera device within a predetermined range around a vehicle to obtain identification information of ground objects including landmarks. Based on the identification information of the ground objects, it determines whether the surrounding environment of the vehicle is a harsh environment for object recognition using the images. If no ground objects are identified within a predetermined distance from the camera device, the surrounding environment of the vehicle is determined to be a harsh environment. Summary of the Invention

[0003] However, in the aforementioned technology, the determination of whether the vehicle's surrounding environment is adverse based on the detection status of landmarks (stationary objects) can lead to a slower response time before the adverse environment is determined, depending on the situation. Specifically, when the vehicle's forward visibility is reduced due to rain splashes or snow kicked up by other vehicles overtaking it (overtaking vehicles) or passing oncoming vehicles, the reduced visibility of landmarks may lead to the determination of an adverse environment. Furthermore, at night and other times, the detection performance of landmarks is inherently prone to deterioration, which may further slow down the response time before determining whether an adverse environment is present, or make it difficult to determine whether an adverse environment is present.

[0004] This disclosure provides a surrounding environment determination device that can accurately and quickly determine whether the surrounding environment of a vehicle is a harsh environment, even in the presence of overtaking or passing vehicles.

[0005] Method 1

[0006] One aspect of this disclosure is a surrounding environment determination device configured to determine the surrounding environment of a vehicle when controlling its high beams. The surrounding environment determination device includes: a surrounding condition detection unit configured to detect the surrounding environmental conditions of the vehicle; an other vehicle detection unit configured to detect whether there are other vehicles overtaking the vehicle or other vehicles meeting the vehicle; and a severe environment determination unit configured to determine whether the surrounding environment of the vehicle is a severe environment based on the surrounding environmental conditions detected by the surrounding condition detection unit and the presence or absence of other vehicles detected by the other vehicle detection unit. The severe environment determination unit is configured to compare a detection score of the surrounding environmental conditions of the vehicle with a severe environment threshold corresponding to the surrounding environmental conditions of the vehicle, and determine whether the surrounding environment of the vehicle is a severe environment based on the comparison result. The severe environment threshold varies depending on the presence or absence of other vehicles.

[0007] Method 2

[0008] Based on method 1 above, the surrounding conditions detection unit can also be configured to detect rain or snow as the environmental condition. Alternatively, the severe environment threshold can vary depending on the presence or absence of other vehicles and the rain or snow conditions.

[0009] Method 3

[0010] Based on method 2 above, the severe environment threshold when other vehicles are present can be smaller than the severe environment threshold when no other vehicles are present. Alternatively, the severe environment threshold for snow can be smaller than the severe environment threshold for rain.

[0011] Method 4

[0012] Based on any of the methods 1 to 3 above, the other vehicle detection unit may also be configured to detect whether other vehicles are within a specified distance from the vehicle. Alternatively, the adverse environment determination unit may be configured to change the adverse environment threshold according to the surrounding environmental conditions of the vehicle when the other vehicle detection unit detects that other vehicles are within a specified distance from the vehicle.

[0013] Method 5

[0014] Based on any of the methods 1 to 4 above, the surrounding environment detection unit may also be configured to use a camera configured to capture images of the vehicle's surroundings to detect the environmental conditions around the vehicle. Alternatively, the other vehicle detection unit may use a camera to detect the presence or absence of other vehicles.

[0015] According to this disclosure, even in the presence of overtaking or passing vehicles, it is possible to determine with high accuracy and speed whether the surrounding environment of the vehicle is a harsh environment. Attached Figure Description

[0016] The features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which the same reference numerals denote the same elements, and wherein:

[0017] Figure 1 This is a schematic structural diagram of a vehicle headlight control device having an ambient environment determination device according to an embodiment of the present disclosure.

[0018] Figure 2 It means by Figure 1 The flowchart shown illustrates the decision-making and control processing steps performed by the ECU.

[0019] Figure 3A This is an example of image data from a camera when an overtaking vehicle passes by the vehicle in front of it.

[0020] Figure 3B This is an example of image data from a camera when an overtaking vehicle passes by the vehicle in front of it.

[0021] Figure 3C This is an example of image data from a camera when an overtaking vehicle passes by the vehicle in front of it.

[0022] Figure 3D This is an example of image data from a camera when an overtaking vehicle passes by the vehicle in front of it.

[0023] Figure 3E This is an example of image data from a camera when an overtaking vehicle passes by the vehicle in front of it.

[0024] Figure 4A It is a chart that, together with the severe environmental threshold, represents the snow condition score when an overtaking vehicle passes the vehicle.

[0025] Figure 4B It is a chart that, together with the severe environmental threshold, represents the snow condition score when an overtaking vehicle passes the vehicle.

[0026] Figure 4C It is a chart that, together with the severe environmental threshold, represents the snow condition score when an overtaking vehicle passes the vehicle.

[0027] Figure 4D It is a chart that, together with the severe environmental threshold, represents the snow condition score when an overtaking vehicle passes the vehicle.

[0028] Figure 4E It is a chart that, together with the severe environmental threshold, represents the snow condition score when an overtaking vehicle passes the vehicle. Detailed Implementation

[0029] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0030] Figure 1 This is a schematic structural diagram of a vehicle headlight control device equipped with a surrounding environment determination device according to an embodiment of the present disclosure. Figure 1 In this embodiment, the vehicle headlight control device 1 is mounted on the vehicle 2, which has an automatic high beam (ADB) function that automatically switches between high and low beams. This disclosure can be applied to autonomous vehicles. The vehicle 2 can also be an autonomous vehicle.

[0031] The vehicle headlight control device 1 is a device that controls two headlights 3 (headlamps) respectively located on the left and right sides of the front of the vehicle 2. The vehicle headlight control device 1 detects the road conditions and surrounding environment in front of the vehicle 2 and controls the headlights 3 to switch from high beam to low beam at the appropriate time. The headlights 3 have a low beam light source 4 and a high beam light source 5.

[0032] The vehicle headlight control device 1 includes a camera 7, a vehicle speed sensor 8, an ADB switch 9, and an ECU (Electronic Control Unit) 10.

[0033] Camera 7 is a camera unit that captures image data of the surroundings of vehicle 2. The surroundings of vehicle 2 include the front, rear, and sides of vehicle 2. Camera 7 may be, for example, a monocular camera or a stereo camera.

[0034] Vehicle speed sensor 8 is a sensor that detects the driving speed (vehicle speed) of vehicle 2. ADB switch 9 is a manual toggle switch used by the driver of vehicle 2 to enable (turn on) or disable (turn off) the automatic high beam function.

[0035] ECU10 consists of a CPU, RAM, ROM, and input / output interfaces. For example, ECU10 loads a program recorded in ROM into RAM, and the CPU executes the program loaded into RAM.

[0036] The ECU10 includes a surrounding environment detection unit 11, an object detection unit 12, an other vehicle determination unit 13, a harsh environment determination unit 14, and a light control unit 15.

[0037] Camera 7, surrounding environment detection unit 11, object detection unit 12, other vehicle determination unit 13, and adverse environment determination unit 14 constitute the surrounding environment determination device 20 of this embodiment. The surrounding environment determination device 20 is a device for determining the surrounding environment of the vehicle 2 when controlling the high beam of the vehicle 2.

[0038] The surrounding environment detection unit 11 detects the environmental conditions around the vehicle 2 based on image data acquired by the camera 7. The surrounding environment detection unit 11, in cooperation with the camera 7, constitutes a surrounding condition detection unit for detecting the environmental conditions around the vehicle 2. That is, the surrounding condition detection unit uses the camera 7 to detect the environmental conditions around the vehicle 2. The surrounding environment detection unit 11 detects the state of rain or snow around the vehicle 2 as the surrounding environmental condition of the vehicle 2. It should be noted that rain includes sleet, hail, and sleet.

[0039] The object detection unit 12 detects objects present around the vehicle 2 based on image data acquired by the camera 7. Objects include other vehicles, two-wheeled vehicles, people, and obstacles.

[0040] Based on the detection results of the object detection unit 12, the other vehicle determination unit 13 determines whether there are other vehicles (overtaking vehicles) that are overtaking this vehicle 2 or other vehicles (passing vehicles) that are meeting this vehicle 2. The other vehicle determination unit 13 determines whether the overtaking vehicle or the passing vehicle is within a specified distance from this vehicle 2.

[0041] The object detection unit 12 and other vehicle determination units 13, together with the camera 7, constitute a vehicle detection unit for detecting whether there are other vehicles overtaking this vehicle 2 or other vehicles meeting this vehicle.

[0042] The adverse environment determination unit 14 determines whether the surrounding environment of the vehicle 2 is an adverse environment based on the environmental conditions around the vehicle 2 detected by the surrounding environment detection unit 11 and the presence or absence of overtaking or meeting vehicles determined by the other vehicle determination unit 13.

[0043] The adverse environment determination unit 14 determines whether the environment surrounding the vehicle 2 is an adverse environment by comparing the detection score of the environmental conditions around the vehicle 2 with the adverse environment threshold corresponding to the environmental conditions around the vehicle 2.

[0044] The severe weather threshold varies depending on the presence of overtaking or passing vehicles and the conditions of rain or snow. The severe weather threshold when overtaking or passing vehicles are present is lower than the severe weather threshold when no overtaking or passing vehicles are present. The severe weather threshold in snow is lower than the severe weather threshold in rain. It should be noted that the severe weather threshold will be explained in detail later.

[0045] If the other vehicle determination unit 13 determines that the overtaking vehicle or the vehicle meeting oncoming traffic is within a specified distance from the vehicle 2, the adverse environment determination unit 14 changes the adverse environment threshold according to the surrounding environmental conditions of the vehicle 2.

[0046] If the automatic high beam function is activated (turned on) via ADB switch 9, the lamp control unit 15 controls the low beam source 4 and high beam source 5 of the headlight 3 by switching between high beam and low beam, based on the environmental conditions around the vehicle 2 detected by the surrounding environment detection unit 11, the detection results of the object detection unit 12, the determination results of the other vehicle determination unit 13, and the vehicle speed of the vehicle 2 detected by the vehicle speed sensor 8. The lamp control unit 15 has a low beam control unit 16 for controlling the low beam source 4 and a high beam control unit 17 for controlling the high beam source 5.

[0047] When the following conditions are met: there are no oncoming vehicles or vehicles traveling in front of vehicle 2; the surrounding area of ​​vehicle 2 is too dark due to the lack of streetlights or other light sources; and vehicle 2 is traveling at a speed above a specified speed, the high beam control unit 17 controls the high beam source 5 to illuminate with high beams. If any of the above three conditions are not met, the high beam control unit 17 controls the high beam source 5 to stop illuminating with high beams.

[0048] When the following conditions are met: there are no oncoming vehicles or vehicles traveling in front of vehicle 2; the surroundings of vehicle 2 are too dark due to the lack of streetlights or other light sources; and vehicle 2 is traveling at a speed exceeding a specified limit, the low beam control unit 16 controls the low beam source 4 to stop low beam illumination. When any of the above three conditions are not met, the low beam control unit 16 controls the low beam source 4 to activate low beam illumination.

[0049] Figure 2 This is a flowchart showing the steps of the decision and control processing performed by ECU10. Figure 2 The process shown is to determine the surrounding environment of the vehicle 2 and control the high beam source 5 based on the determination result.

[0050] exist Figure 2 In step S10, ECU10 first detects the presence of other vehicles based on image data from camera 7 (step S101). Additionally, ECU10 detects rain or snow conditions based on image data from camera 7 (step S102). Next, considering the other vehicles detected in step S101, ECU10 determines whether an overtaking vehicle or a vehicle meeting oncoming traffic is detected (step S103).

[0051] When ECU10 determines that no overtaking vehicles or oncoming vehicles are detected, it determines whether the snow condition score detected in step S102 is above the severe environment threshold Pa for no other vehicles (step S104).

[0052] The snow condition score is one of the scores for detecting the environmental conditions surrounding vehicle 2. The snow condition score represents the snow condition in front of vehicle 2 as a numerical value. The more snow in front of vehicle 2, the higher the snow condition score. The severe snow environment threshold Pa (no other vehicles) is the threshold for severe snow conditions when there are no overtaking or passing vehicles. For example, the severe snow environment threshold Pa (no other vehicles) is 30.

[0053] When the ECU10 determines that the snow condition score is above the severe environment threshold Pa for snow-free conditions with no other vehicles, it determines that the surrounding environment of vehicle 2 is a severe environment (step S105). Then, the ECU10 controls the high beam source 5 to turn off the high beam (step S106) and executes the above step S101 again.

[0054] If the ECU10 determines in step S104 that the snow condition score is not above the severe environment threshold Pa for snow without other vehicles, it determines whether the rain condition score detected in step S102 is above the severe environment threshold Pb for rain without other vehicles (step S107).

[0055] The rain condition score is another score for detecting the environmental conditions surrounding vehicle 2. The rain condition score represents the rain condition in front of vehicle 2 as a numerical value. The more rain in front of vehicle 2, the higher the rain condition score. The severe rain environment threshold Pb for no other vehicles is the threshold for severe rain environments when there are no overtaking or passing vehicles. For example, the severe rain environment threshold Pb for no other vehicles is 40.

[0056] In snowy weather, visibility ahead of vehicle 2 is more likely to be poor compared to rainy weather. Therefore, in order to more easily determine a snowy scene as a severe environment than a rainy scene, the severe environment threshold Pa for snow without other vehicles is lower than the severe environment threshold Pb for rain without other vehicles.

[0057] When the ECU10 determines that the rain condition score is above the severe environment threshold Pb for rain-free conditions, it determines that the surrounding environment of vehicle 2 is a severe environment (step S105). Then, the ECU10 controls the high beam source 5 to turn off the high beam (step S106) and executes the above step S101 again.

[0058] If the score for determining that it is raining is not above the severe environment threshold Pb for rain-free conditions with no other vehicles, ECU10 determines that the surrounding environment of vehicle 2 is not a severe environment (step S108). Then, ECU10 controls the high beam source 5 to turn on the high beam (step S109) and executes step S101 again.

[0059] When ECU10 determines in step S103 that an overtaking vehicle or a vehicle meeting oncoming traffic has been detected, it determines whether the overtaking vehicle or the vehicle meeting oncoming traffic is within a specified distance from vehicle 2 (step S110). The specified distance is, for example, 30m. If ECU10 determines that the overtaking vehicle or the vehicle meeting oncoming traffic is not within the specified distance from vehicle 2, it executes the steps after step S104 described above.

[0060] When ECU10 determines that an overtaking vehicle or a vehicle that is about to pass is within a specified distance from vehicle 2, it determines whether the overtaking vehicle or the vehicle that is about to pass is within one lane to the left or right of vehicle 2 (step S111). When ECU10 determines that the overtaking vehicle or the vehicle that is about to pass is not within one lane to the left or right of vehicle 2, it executes the steps after step S104 above.

[0061] When ECU10 determines that an overtaking or oncoming vehicle is within approximately one lane of its own vehicle (approximately 2 lanes away), it determines whether the snow condition score detected in step S102 is above the severe snow environment threshold Qa for the presence of other vehicles (step S112). The severe snow environment threshold Qa for the presence of other vehicles is the severe snow environment threshold for the presence of overtaking or oncoming vehicles. For example, the severe snow environment threshold Qa for the presence of other vehicles is 10.

[0062] When overtaking or oncoming vehicles approach vehicle 2, the snow can be kicked up by these vehicles, potentially causing poor visibility in front of vehicle 2. Therefore, in order to easily determine a severe environment when overtaking or oncoming vehicles are within one lane to the left or right of vehicle 2, the severe environment threshold Qa for snow with other vehicles is made lower than the severe environment threshold Pa for snow without other vehicles.

[0063] When the ECU10 determines that the snow condition score is above the severe environment threshold Qa for other vehicles, it determines that the surrounding environment of vehicle 2 is a severe environment (step S105). Then, the ECU10 controls the high beam source 5 to turn off the high beam (step S106) and executes the above step S101 again.

[0064] If the ECU10 determines in step S112 that the snow condition score is not above the severe weather threshold Qa for snow with other vehicles, it then determines whether the rain condition score detected in step S102 is above the severe weather threshold Qb for rain with other vehicles (step S113). The severe weather threshold Qb for rain with other vehicles is the severe weather threshold for rain when there are overtaking or passing vehicles. The severe weather threshold Qb for rain with other vehicles is 20.

[0065] When overtaking or oncoming vehicles approach vehicle 2, the water splashed up by these vehicles can easily obstruct the vehicle's forward visibility. Therefore, in order to easily classify an adverse environment as one lane away from vehicle 2 when overtaking or oncoming vehicles are within one lane to the left or right, the adverse environment threshold Qb for rain with other vehicles is made smaller than the adverse environment threshold Pb for rain without other vehicles.

[0066] Furthermore, snow is lighter than rain. Therefore, swirling snow stays in the air for a longer period than swirling rain. Consequently, it is generally believed that the duration of impaired forward visibility due to swirling snow is longer than that due to swirling rain. Therefore, to more easily classify snow scenes as adverse environments than rain scenes, the adverse environment threshold Qa for snow scenes with other vehicles is lower than the adverse environment threshold Qb for rain scenes with other vehicles.

[0067] When the ECU10 determines that the rain condition score is above the severe environment threshold Qb for rainy conditions caused by other vehicles, it determines that the surrounding environment of vehicle 2 is a severe environment (step S105). Then, the ECU10 controls the high beam source 5 to turn off the high beam (step S106) and executes the above step S101 again.

[0068] If the ECU10 determines that the rain condition score is not above the severe environment threshold Qb for rainy conditions of other vehicles, it determines that the surrounding environment of vehicle 2 is not a severe environment (step S108). Then, the ECU10 controls the high beam source 5 to turn on the high beam (step S109) and executes the above step S101 again.

[0069] Here, the surrounding environment detection unit 11 executes step S102. The object detection unit 12 executes step S101. The other vehicle determination unit 13 executes steps S103, S110, and S111. The adverse environment determination unit 14 executes steps S104, S105, S107, S108, S112, and S113. The high beam control unit 17 of the light control unit 15 executes steps S106 and S109.

[0070] In the vehicle headlight control device 1 described above, when driving on a snow track at night, if there are no oncoming or forward vehicles in front of the vehicle 2, and the area around the vehicle 2 is dark, and the vehicle 2 is traveling at a speed above a certain limit, the high beam of the headlight 3 is turned on.

[0071] In such a state, such as Figure 3AAs shown, if there is an overtaking vehicle A in the lane to the right of vehicle 2's current driving lane, the system determines whether the surrounding environment of vehicle 2 is a severe environment by comparing the snow condition score with the severe environment threshold Qa (where other vehicles are in snow). In this case, if... Figure 4A As shown, if the snow condition score is lower than the severe environment threshold Qa for other vehicles in snowy conditions, the surrounding environment of vehicle 2 is determined not to be a severe environment. Furthermore, overtaking vehicle A is not yet traveling in front of vehicle 2. Therefore, the high beam of the headlights 3 remains on.

[0072] After that, as Figure 3B As shown, vehicle 2 is overtaken by vehicle A. At this time, as... Figure 4B As shown, with the snow condition score remaining unchanged, the snow condition score is lower than the severe environment threshold Qa for other vehicles in snowy conditions, therefore, the surrounding environment of vehicle 2 is determined not to be a severe environment. However, overtaking vehicle A is traveling in front of vehicle 2. Therefore, the high beam of the headlight 3 is switched from the on state to the off state.

[0073] After that, as Figure 3C As shown, because vehicle A overtook vehicle 2, it kicked up snow from the road. Therefore, as... Figure 4C As shown, the snow condition score increases, but it is still lower than the severe environment threshold Qa for snow conditions involving other vehicles. Therefore, the surrounding environment of vehicle 2 is determined not to be a severe environment. Additionally, since overtaking vehicle A is traveling in front of vehicle 2, the high beams of the headlights 3 remain off.

[0074] After that, as Figure 3D As shown, the visibility ahead of vehicle 2 is reduced due to the swirling snow. Therefore, as... Figure 4D As shown, the snow condition score increases further. Moreover, if the snow condition score is higher than the severe environment threshold Qa for other vehicles, the surrounding environment of vehicle 2 is determined to be a severe environment. Therefore, regardless of whether there is an overtaking vehicle A traveling in front of vehicle 2, the high beam of the headlights 3 remains off.

[0075] After that, as Figure 3E As shown, due to the swirling snow, the visibility ahead of vehicle 2 has further deteriorated, and the streetlights and traffic lights ahead of vehicle 2 are barely visible. Therefore, as... Figure 4E As shown, the snow condition score increases further. In this case, the snow condition score is also higher than the severe environment threshold Qa for other vehicles in snow, so the surrounding environment of vehicle 2 is determined to be a severe environment, and the high beam of the headlight 3 is kept off.

[0076] Incidentally, when there are overtaking or passing vehicles, the recognition performance of camera 7 becomes unstable due to rain spray or snow. Therefore, even when there are oncoming or advancing vehicles in front of vehicle 2, high beams may still be shining in front of vehicle 2. Therefore, it is necessary to determine whether the surrounding environment of vehicle 2 is adverse.

[0077] However, in snowy weather, when determining whether the surrounding environment of vehicle 2 is a severe environment by comparing the snow condition score with the severe environment threshold Pa for no other vehicles in snow, the following problem arises.

[0078] That is, even if the visibility in front of vehicle 2 is reduced due to the snow being kicked up (see reference). Figure 3D However, since the snow condition score is lower than the severe environment threshold Pa for no other vehicles in snow, the surrounding environment of vehicle 2 is determined not to be a severe environment (refer to...). Figure 4D Furthermore, due to the reduced visibility ahead of vehicle 2 caused by the swirling snow, camera 7 failed to detect overtaking vehicle A, even though the overtaking vehicle A was traveling in front of vehicle 2. As a result, the high beam of headlight 3 switched from off to on.

[0079] Subsequently, if the streetlights and traffic lights ahead of vehicle 2 become barely visible (refer to...) Figure 3E Since the snow condition score is higher than the severe environment threshold Pa for no other vehicles in snow, the surrounding environment of vehicle 2 is judged to be a severe environment (refer to...). Figure 4E Therefore, the high beam of headlight 3 switched from the on state to the off state.

[0080] On the other hand, in this embodiment, when overtaking vehicle A is present, the surrounding environment of vehicle 2 is determined to be a harsh environment by comparing the snow condition score with the harsh environment threshold Qa (where there are other vehicles and snow) which is smaller than the harsh environment threshold Pa (where there are no other vehicles and snow). Therefore, if the visibility ahead of vehicle 2 is worsened due to the snow kicked up by overtaking vehicle A as it passes by, it is easy to determine that the surrounding environment of vehicle 2 is a harsh environment. Consequently, even if camera 7 fails to detect overtaking vehicle A due to poor visibility ahead of vehicle 2, the high beam of headlight 3 is turned off.

[0081] As described above, according to this embodiment, the environmental conditions surrounding the vehicle 2 are detected, and the presence of other vehicles overtaking the vehicle 2 (overtaking vehicles) or meeting the vehicle 2 (meeting vehicles) is detected. Then, by comparing the detection score of the environmental conditions surrounding the vehicle 2 with a severe environmental threshold corresponding to the environmental conditions surrounding the vehicle 2, it is determined whether the environment surrounding the vehicle 2 is a severe environment. By comparing the environmental condition detection score with the severe environmental threshold corresponding to the environmental condition, it is possible to quickly determine whether the environment surrounding the vehicle 2 is a severe environment. Here, the severe environmental threshold varies depending on whether there are overtaking vehicles or meeting vehicles. Therefore, by comparing the environmental condition detection score with the severe environmental threshold corresponding to the presence or absence of overtaking vehicles or meeting vehicles, it is possible to determine with high accuracy whether the environment surrounding the vehicle 2 is a severe environment. Based on the above, even in the presence of overtaking vehicles or meeting vehicles, it is possible to determine with high accuracy and speed whether the environment surrounding the vehicle 2 is a severe environment. As a result, it is possible to suppress situations where other vehicles are shining high beams at the front of the vehicle 2 even when they are traveling in front of the vehicle 2.

[0082] Furthermore, in this embodiment, the state of rain or snow is detected as the environmental condition surrounding the vehicle 2, and the severe environment threshold varies depending on whether there are overtaking or passing vehicles and the state of rain or snow. Therefore, in rainy or snowy weather, when overtaking or passing vehicles are present, and based on the anticipation that the visibility ahead of the vehicle 2 will be reduced due to the swirling rain or snow, it is determined whether the surrounding environment of the vehicle 2 is a severe environment. Thus, even in rainy or snowy weather, it is possible to determine with high accuracy whether the surrounding environment of the vehicle 2 is a severe environment.

[0083] Furthermore, when overtaking vehicles pass vehicle 2 or when oncoming vehicles pass vehicle 2, rain or snow is easily kicked up, resulting in poor forward visibility for vehicle 2. Additionally, snow takes longer to be kicked up compared to rain. Therefore, in snowy weather, the duration of poor forward visibility for vehicle 2 tends to be longer than in rainy weather. Therefore, in this embodiment, by making the adverse environment threshold for the presence of overtaking or oncoming vehicles smaller than the adverse environment threshold for the absence of overtaking or oncoming vehicles, and by making the adverse environment threshold for snow conditions smaller than the adverse environment threshold for rain conditions, it is possible to determine with greater accuracy whether the surrounding environment of vehicle 2 is an adverse environment in rainy or snowy weather.

[0084] Furthermore, in this embodiment, when an overtaking or oncoming vehicle is detected within a predetermined distance of vehicle 2, the adverse environment threshold is adjusted based on the surrounding environmental conditions of vehicle 2. If the overtaking or oncoming vehicle is farther from vehicle 2 than the predetermined distance, the adverse environment threshold is not adjusted. Therefore, in rainy or snowy weather, when it is difficult to determine that the visibility ahead of vehicle 2 is poor due to the overtaking or oncoming vehicle being far away, the surrounding environment of vehicle 2 is unlikely to be considered an adverse environment. Thus, the unnecessary ignition of high beams towards the front of vehicle 2 can be suppressed.

[0085] Furthermore, in this embodiment, a camera 7 that captures images of the surroundings of the vehicle 2 is used to detect the environmental conditions around the vehicle 2 and the presence or absence of overtaking or passing vehicles. By using the camera 7 that captures images of the surroundings of the vehicle 2, the detection of the environmental conditions around the vehicle 2 and the presence or absence of overtaking or passing vehicles can be achieved with simple processing and low cost.

[0086] It should be noted that this disclosure is not limited to the above-described embodiments. For example, in the above-described embodiments, the environmental conditions surrounding the vehicle 2 are detected as rain or snow, but in addition to rain or snow, conditions such as dense fog may also be detected.

[0087] In addition, in the above embodiment, a camera 7 that captures images of the surroundings of the vehicle 2 is used to detect whether there are overtaking vehicles or oncoming vehicles, but it is not particularly limited to this method. For example, a ranging sensor such as LiDAR can also be used to detect whether there are overtaking vehicles or oncoming vehicles.

[0088] In addition, in the above embodiment, a camera 7 that captures images of the surroundings of the vehicle 2 is used to detect the state of rain or snow, but it is not particularly limited to this method. The camera 7 may be used instead of the camera 7 or together with the camera 7 to detect the state of rain or snow based on information about the operation of the windshield wipers.

Claims

1. A device for determining the surrounding environment, characterized in that, The surrounding environment determination device is configured to determine the surrounding environment of the vehicle when controlling the high beams of the vehicle. The surrounding environment determination device includes: The surrounding environment detection unit is configured to detect the environmental conditions surrounding the vehicle. The other vehicle detection unit is configured to detect whether there are other vehicles overtaking the vehicle or other vehicles meeting the vehicle. as well as The adverse environment determination unit is configured to determine whether the surrounding environment of the vehicle is an adverse environment based on the environmental conditions around the vehicle detected by the surrounding condition detection unit and the presence or absence of other vehicles detected by the other vehicle detection unit. The severe environment determination unit is configured to: compare the detection score of the environmental conditions surrounding the vehicle with a severe environment threshold corresponding to the environmental conditions surrounding the vehicle, and determine whether the surrounding environment of the vehicle is a severe environment based on the comparison result. The severe environment threshold varies depending on the presence or absence of the other vehicles.

2. The surrounding environment determination device according to claim 1, characterized in that, The surrounding environment detection unit is configured to detect the state of rain or snow as the environmental condition. The severe environment threshold varies depending on the presence or absence of the other vehicles and the state of rain or snow.

3. The surrounding environment determination device according to claim 2, characterized in that, The severe environment threshold when the other vehicles are present is smaller than the severe environment threshold when the other vehicles are not present. The severe environmental threshold for the snow state is smaller than the severe environmental threshold for the rain state.

4. The surrounding environment determination device according to claim 1, characterized in that, The other vehicle detection unit is configured to detect whether the other vehicles are within a specified distance of the current vehicle. The severe environment determination unit is configured to change the severe environment threshold according to the surrounding environmental conditions of the vehicle when the other vehicle detection unit detects that the other vehicle exists within the specified distance of the vehicle.

5. The surrounding environment determination device according to claim 1, characterized in that, The surrounding environment detection unit is configured to use a camera configured to capture images of the vehicle's surroundings to detect the environmental conditions around the vehicle. The other vehicle detection unit uses the camera to detect the presence or absence of other vehicles.

Images