Surrounding environment detection processing device, surrounding environment detection processing method, and recording medium

Abstract

This surrounding environment detection processing device detects the surrounding environment of a vehicle on the basis of measurement information from a plurality of surrounding environment sensors having different measurement ranges and includes a storage unit in which information regarding the measurement range of each surrounding environment sensor, information regarding a coverage rate indicating the ratio of the measurement range of one or more of the surrounding environment sensors to all the measurement ranges measured by all the surrounding environment sensors, and information regarding an overlap rate at which the measurement ranges of two or more of the surrounding environment sensors overlap each other are recorded. The weights of the coverage rate and the overlap rate are set in accordance with the traveling environment of the vehicle, and one or more surrounding environment sensors to be used for detecting the surrounding environment are selected using the weights.

Description

Surrounding environment detection processing device, surrounding environment detection processing method, and recording medium

[0001] The present disclosure relates to a surrounding environment detection processing device, a surrounding environment detection processing method, and a recording medium.

[0002] Electric vehicles are known that run by using power stored in a battery to drive a drive motor. One of the important issues for electric vehicles is ensuring the cruising distance that can be traveled before the battery runs out.

[0003] Possible solutions to the above issues include, for example, increasing battery capacity to expand power resources, or limiting power consumption through power management. Among these, one method of limiting power consumption is to use a battery controller to manage charging and discharging, but as the development of autonomous electric vehicles progresses, it will become necessary to coordinate power control by the battery controller with the power consumption required for driving assistance functions.

[0004] JP 2022-18853 A JP 2015-55947 A

[0005] It is known that various sensors in autonomous vehicles and devices that process the measurement signals of these sensors consume a large amount of power. On the other hand, if these various sensors and processing devices are not installed, autonomous driving and driving assistance functions aimed at improving safety cannot be performed. For example, when the remaining battery capacity (SOC: State of Charge) is low and there is no charging station nearby, it is necessary to extend the vehicle's range by cutting off the power supplied to the autonomous driving devices and transferring driving authority to the driver.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and an object of the present disclosure is to provide a surrounding environment detection processing device, a surrounding environment detection processing method, and a recording medium that are capable of achieving both the range and driving assistance functions of an electric vehicle that runs using power charged in a battery for a long period of time.

[0007] In order to solve the above problem, according to one aspect of the present disclosure, there is provided an ambient environment detection processing device that detects the ambient environment of a vehicle based on measurement information from multiple ambient environment sensors with different measurement ranges, the device having a memory unit that records information on the measurement ranges of each of the ambient environment sensors, information on a coverage rate that indicates the proportion of the measurement range of one or more of the ambient environment sensors to the total measurement range measured by all of the ambient environment sensors, and information on an overlap rate at which the measurement ranges of two or more of the ambient environment sensors overlap with each other, and the ambient environment detection processing device sets weights for each of the coverage rate and the overlap rate according to the driving environment of the vehicle, and uses the weights to select one or more of the ambient environment sensors to use for detecting the ambient environment.

[0008] In addition, according to another aspect of the present disclosure to solve the above problem, there is provided an ambient environment detection processing method for detecting the ambient environment of a vehicle based on measurement information from multiple ambient environment sensors with different measurement ranges, in which a computer refers to information on the measurement ranges of each of the ambient environment sensors, information on a coverage rate indicating the proportion of the measurement range of one or more of the ambient environment sensors to the total measurement range measured by all of the ambient environment sensors, and information on an overlap rate at which the measurement ranges of two or more of the ambient environment sensors overlap with each other, and sets weights for each of the coverage rate and the overlap rate in accordance with the driving environment of the vehicle, and uses the weights to select one or more of the ambient environment sensors to use for detecting the ambient environment.

[0009] In addition, according to another aspect of the present disclosure, in order to solve the above problem, a non-transitory tangible recording medium is provided that records a program that causes a computer to refer to information on the measurement ranges of each of a plurality of ambient environment sensors having different measurement ranges, information on coverage rates that indicate the proportion of the measurement ranges of one or more of the ambient environment sensors to the total measurement range measured by all of the ambient environment sensors, and information on overlap rates at which the measurement ranges of two or more of the ambient environment sensors overlap with each other, and to set weights for each of the coverage rates and overlap rates in accordance with the driving environment of the vehicle, and to select one or more of the ambient environment sensors to use for detecting the surrounding environment using the weights.

[0010] As described above, according to the present disclosure, it is possible to achieve both a long-term cruising range and driving assistance functions for an electric vehicle that runs using power charged in a battery.

[0011] FIG. 1 is an explanatory diagram schematically illustrating a system configuration for running a vehicle equipped with a surrounding environment detection processing device according to an embodiment of the present disclosure. FIG. 1 is an explanatory diagram schematically illustrating a system configuration for detecting the surrounding environment of a vehicle equipped with a surrounding environment detection processing device according to the same embodiment. FIG. 2 is a block diagram illustrating a system configuration of a vehicle equipped with a surrounding environment detection processing device according to the same embodiment. FIG. 3 is an explanatory diagram schematically illustrating the measurement ranges of each surrounding environment sensor. FIG. 4 is an explanatory diagram illustrating the measurement ranges of each surrounding environment sensor. FIG. 5 is an explanatory diagram illustrating a method for calculating the coverage of the measurement range of a surrounding environment sensor whose main measurement range is a forward area by the surrounding environment detection processing device according to the same embodiment. FIG. 6 is a flowchart illustrating a routine of processing operations by the surrounding environment detection processing device according to the same embodiment. FIG. 7 is a flowchart illustrating a routine of display processing by the surrounding environment detection processing device according to the same embodiment. FIG. 8 is an explanatory diagram illustrating the initial setting of a combination of surrounding environment sensors when a vehicle is running on a highway. FIG. 9 is an explanatory diagram illustrating the initial setting of a combination of surrounding environment sensors when a vehicle is running on a main road. FIG. 10 is an explanatory diagram illustrating the initial setting of a combination of surrounding environment sensors when a vehicle is running on a suburban road. FIG. 11 is an explanatory diagram illustrating the initial setting of a combination of surrounding environment sensors when a vehicle is running on an urban road. FIG. 12 is a flowchart illustrating the calculation processing of weight setting elements by the surrounding environment detection processing device according to the same embodiment. FIG. 10 is an explanatory diagram showing an example of a method for calculating an object occupancy rate by the surrounding environment detection processing device according to the embodiment. FIG. 11 is an explanatory diagram showing an example of weight setting information set according to the object occupancy rate in the embodiment. FIG. 12 is a flowchart showing the calculation process of weight setting elements by the surrounding environment detection processing device according to a second embodiment. FIG. 13 is an explanatory diagram showing an example of weight setting information set according to the frequency of accidents and the type of accident in the embodiment. FIG. 14 is a flowchart showing the calculation process of weight setting elements by the surrounding environment detection processing device according to a third embodiment. FIG. 14 is an explanatory diagram showing an example of a method for calculating a blind spot occupancy rate by the surrounding environment detection processing device according to the embodiment. FIG. 15 is an explanatory diagram showing an example of weight setting information set according to the blind spot occupancy rate in the embodiment. FIG. 16 is a flowchart showing the calculation process of weight setting elements by the surrounding environment detection processing device according to a fourth embodiment. FIG. 17 is an explanatory diagram showing an example of weight setting information set according to the type of object and the number of types of objects in the embodiment.10 is a flowchart illustrating a calculation process of a weight setting element according to an application example of an embodiment of the present disclosure.

[0012] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0013] In the embodiments described below, "autonomous driving" includes not only fully autonomous driving in which a computer performs all of the vehicle's driving operations, but also driving assistance functions in which a computer performs some of the vehicle's driving operations and driving assistance functions in which a computer temporarily intervenes in the vehicle's driving operations.

[0014] <<1. First embodiment>> <1-1. Overall configuration of vehicle> First, an example of a system configuration of a vehicle to which a vehicle control device according to an embodiment of the present disclosure is applied will be described.

[0015] 1 to 3 are diagrams for explaining the system configuration of vehicle 1. Fig. 1 is an explanatory diagram that schematically shows the system configuration for driving vehicle 1, Fig. 2 is an explanatory diagram that schematically shows the system configuration for detecting the surrounding environment of vehicle 1, and Fig. 3 is a block diagram that shows the system configuration of vehicle 1.

[0016] Vehicle 1 is an electric vehicle that runs using drive torque output from a drive motor 2. As shown in Fig. 1, vehicle 1 is configured as a two-wheel drive four-wheel vehicle in which drive torque output from drive motor 2 is transmitted to left and right front wheels via a differential 4. Vehicle 1 may also be a four-wheel drive vehicle in which drive torque is transmitted to front and rear wheels. Vehicle 1 may also be an electric vehicle equipped with two drive motors, a front-wheel drive motor and a rear-wheel drive motor, or an electric vehicle equipped with drive motors corresponding to each wheel.

[0017] The vehicle 1 includes, as components for driving the vehicle 1, a drive motor 2, an inverter 3, a differential 4, an electric steering device 6, a brake control unit 7, a high-voltage battery 8, a low-voltage battery 39, and a vehicle control unit 41. The vehicle control unit 41 is a control unit made up of one or more electronic control units (ECUs), and controls the operation of the drive motor 2, the electric steering device 6, and the brake control unit 7. The vehicle control unit 41 is connected to a surrounding environment detection processing device 50 so as to be able to communicate with the surrounding environment detection processing device 50.

[0018] The vehicle control unit 41 acquires information about the operation state and behavior of the vehicle 1 measured by the vehicle state sensors 33. The vehicle state sensors 33 include, for example, a wheel speed sensor, an acceleration sensor, an angular velocity sensor, a steering angle sensor, an accelerator opening sensor, a brake stroke sensor, and a brake pressure sensor. The vehicle state sensors 33 output sensor signals indicating the detected information to the vehicle control unit 41.

[0019] The inverter 3 is controlled by the vehicle control unit 41 to control the power supplied from the high-voltage battery 8 to the drive motor 2. The inverter 3 is also controlled by the vehicle control unit 41 to control the power generated by the drive motor 2 and charged to the high-voltage battery 8. When an autonomous driving function or a driving assistance function is being executed, the vehicle control unit 41 sets a target drive torque or a target regenerative torque and controls the drive of the inverter 3. During manual driving, the vehicle control unit 41 sets a target drive torque or a target regenerative torque based on the accelerator opening and brake stroke operated by the driver and controls the drive of the inverter 3.

[0020] The electric steering device 6 includes an electric motor and a gear mechanism (not shown), and adjusts the steering angle of the front wheels by being controlled by the vehicle control unit 41. When an automatic driving function or a driving assistance function is being executed, the vehicle control unit 41 sets a target steering angle or a target steering angular velocity, and controls the driving of the electric steering device 6. During manual driving, the vehicle control unit 41 sets a target steering angle or a target steering angular velocity based on the steering angle of the steering wheel 5 operated by the driver, and controls the driving of the electric steering device 6.

[0021] The brake control unit 7 is controlled by the vehicle control unit 41 to control the hydraulic pressure supplied to the wheel cylinders provided on each wheel, thereby controlling the braking force of the vehicle 1. When an automatic driving function or a driving assistance function is being executed, the vehicle control unit 41 sets a target braking torque and controls the operation of the brake control unit 7. During manual driving, the vehicle control unit 41 sets a target braking torque based on the brake stroke operated by the driver and controls the operation of the brake control unit 7. The braking force adjusted by the brake control unit 7 is used in combination with the regenerative braking force generated by the drive motor 2.

[0022] 2, in this embodiment, the surrounding environment sensors include a long-range front camera 11, a short-range front camera 13 (13L, 13R), a right front camera 15R, a left front camera 15L, a right rear camera 17R, a left rear camera 17L, a long-range rear camera 19, a short-range rear camera 21, a LiDAR (Light Detection and Ranging) 23, a right side radar 25R, a left side radar 25L, and ultrasonic sensors 27 provided at the center and on the left and right sides of the front and rear of the vehicle.

[0023] The camera includes an imaging element such as a CCD (Charged Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor), and transmits generated image data to the surrounding environment detection processing device 50. In the vehicle 1 shown in FIG. 2 , the short-range front camera 13 is configured as a stereo camera including a pair of left and right cameras 13L, 13R. The LiDAR 23 emits laser light and receives reflected light, and transmits frame data in which each reflection point is mapped in three-dimensional space to the surrounding environment detection processing device 50. The right side radar 25R and the left side radar 25L are, for example, millimeter-wave radars, which emit radar waves and receive reflected waves, and transmit frame data in which each reflection point is mapped in three-dimensional space to the surrounding environment detection processing device 50. The ultrasonic sensor 27 emits ultrasonic waves and receives reflected waves, and transmits information indicating the distance to each reflection point to the surrounding environment detection processing device 50.

[0024] The vehicle 1 also includes a position information sensor 31 and a notification device 43. The position information sensor 31 receives satellite signals from positioning satellites of a Global Navigation Satellite System (GNSS), such as the Global Positioning System (GPS). The position information sensor 31 transmits the position information of the vehicle 1 contained in the received satellite signals to the surrounding environment detection processing device 50. Note that the position information sensor 31 may include a sensor, other than a GPS sensor, that receives satellite signals from other satellite systems to identify the position of the vehicle 1.

[0025] The notification device 43 is driven by the surrounding environment detection processing device 50 and notifies the driver of various information by means of image display, audio output, etc. The notification device 43 includes, for example, a display device provided in the instrument panel and a speaker provided in the vehicle 1. The display device may be a display device that displays information from a navigation system. The notification device 43 may also include a HUD (head-up display) that displays information on the front window superimposed on the scenery around the vehicle 1.

[0026] The high-voltage battery 8 that supplies power to the drive motor 2 is, for example, a battery rated at 200 V or 48 V. The high-voltage battery 8 is equipped with a battery management system (BMS) 9 that measures or estimates the SOC, voltage, current, temperature, etc. of the high-voltage battery 8. Information on the state of the high-voltage battery 8 obtained by the BMS 9 is sent to the surrounding environment detection processing device 50.

[0027] The low-voltage battery 39 is, for example, a battery rated at 12 V. The low-voltage battery 39 supplies power to various sensors, control devices, and other electronic devices excluding the drive motor 2. The low-voltage battery 39 is connected to the high-voltage battery 8 via a step-down converter 37, and the power output from the high-voltage battery 8 is stepped down and charged into the low-voltage battery 39. The surrounding environment detection processing device 50 is configured to be able to acquire information on the voltage of the low-voltage battery 39.

[0028] <1-2. Surrounding environment detection processing device> Next, a specific description will be given of the surrounding environment detection processing device 50 according to this embodiment. The surrounding environment detection processing device 50 according to this embodiment has a configuration that selects one or more surrounding environment sensors to be used for detecting the surrounding environment by performing a weighting calculation according to the proportion of the area around the vehicle 1 where objects exist (object occupancy rate).

[0029] (1-2-1. Configuration Example) The surrounding environment detection processing device 50 functions as a device that detects the surrounding environment of the vehicle 1 by having one or more processors, such as CPUs (Central Processing Units), execute a computer program. The computer program is a computer program that causes the processor to execute the operations, described below, that should be performed by the surrounding environment detection processing device 50. The computer program executed by the processor may be recorded on a recording medium that functions as a storage unit (memory) 53 provided in the surrounding environment detection processing device 50, or may be recorded on a recording medium built into the surrounding environment detection processing device 50 or any recording medium that can be externally attached to the surrounding environment detection processing device 50.

[0030] The recording medium for recording a computer program may be a magnetic medium such as a hard disk, a floppy disk, or a magnetic tape; an optical recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD (Digital Versatile Disc), or a Blu-ray (registered trademark); a magneto-optical medium such as a floptical disk; a memory element such as a RAM or a ROM; a flash memory such as a USB (Universal Serial Bus) memory or an SSD (Solid State Drive); or any other medium capable of storing a program.

[0031] 3 , a plurality of surrounding environment sensors are connected to the surrounding environment detection processing device 50 via a dedicated line or communication means such as a controller area network (CAN) or local internet (LIN). The surrounding environment detection processing device 50 is also connected to a BMS 9, a position information sensor 31, a vehicle control unit 41, and a notification device 43.

[0032] The surrounding environment detection processing device 50 is not limited to an electronic control device mounted on the vehicle 1, but may be a terminal device capable of wireless or wired communication.

[0033] The surrounding environment detection processing device 50 includes a processing unit 51, a storage unit 53, a sensor information storage unit 55, and a map data storage unit 57. The processing unit 51 is configured with one or more processors such as a CPU and various peripheral components. Part or all of the processing unit 51 may be configured with updatable firmware or the like, or may be a program module or the like executed by instructions from the CPU or the like.

[0034] (Storage Unit) The storage unit 53 is composed of one or more storage elements such as RAM or ROM connected to the processing unit 51 so as to be able to communicate with it. However, the type and number of storage units 53 are not particularly limited. The storage unit 53 stores information such as computer programs executed by the processing unit 51, various parameters used in arithmetic processing, maps, detection data, and arithmetic results. A part of the storage unit 53 is used as a work area for the processing unit 51.

[0035] (Sensor Information Storage Unit) The sensor information storage unit 55 is configured with a storage element such as RAM or ROM communicably connected to the processing unit 51, or a storage medium such as an HDD, CD, DVD, SSD, USB flash, or storage device. The sensor information storage unit 55 stores information on the measurement ranges of each of the multiple ambient environment sensors, as well as information on the power consumption of each ambient environment sensor, information on the measurement range of each ambient environment sensor, information on the coverage rate indicating the ratio of the measurement range of one or more ambient environment sensors to the entire measurement range measured by all the ambient environment sensors, and information on the overlap rate, which is the rate at which the measurement ranges of two or more ambient environment sensors overlap with each other.

[0036] 4 and 5 are explanatory diagrams that schematically show the measurement ranges of the respective surrounding environment sensors shown in FIG. 2. Measurement range DA1 represents the measurement range of the long-range front camera 11. Measurement range DA2 represents the measurement range of the short-range front camera 13. Measurement range DA3 represents the measurement range of the right front camera 15R. Measurement range DA4 represents the measurement range of the left front camera 15L. Measurement range DA5 represents the measurement range of the right rear camera 17R. Measurement range DA6 represents the measurement range of the left rear camera 17L. Measurement range DA7 represents the measurement range of the long-range rear camera 19. Measurement range DA8 represents the measurement range of the short-range rear camera 21. Measurement range DA9 represents the measurement range of the LiDAR 23. Measurement range DA10 represents the measurement range of the right-side directional radar 25R. Measurement range DA11 represents the measurement range of the left-side directional radar 25L. The measurement range DA12 represents the measurement range of each ultrasonic sensor 27.

[0037] As shown in Fig. 4, a portion of the measurement range of each ambient environment sensor overlaps with the measurement range of one or more other ambient environment sensors. Note that Fig. 4 is intended to clearly show that the measurement ranges of the ambient environment sensors partially overlap, and the angle range, depth, etc. of the illustrated measurement ranges differ from the actual measurement ranges.

[0038] The sensor information storage unit 55 stores information about the measurement range of each surrounding environment sensor. The information about the measurement range includes the position of the origin of the measurement range of the surrounding environment sensor, the measurement direction (direction of the central axis), the measurable angle, and the measurable distance. The position of the origin of the measurement range may be, for example, a coordinate position on a coordinate system whose origin is a predetermined position of the vehicle 1.

[0039] The sensor information storage unit 55 also stores information about the power consumption of each ambient environment sensor when it is operated. The power consumption information may be stored as power consumption per unit time (e.g., kWh), or may be information indicating the ratio of power consumption per unit time according to the operating state of the ambient environment sensor, with the power consumption per unit time when each ambient environment sensor is operated at maximum output as a reference (e.g., 100%). In this embodiment, the ultrasonic sensor 27 that detects objects at close range is set to operate at a constant power consumption at all times, and therefore a constant value is stored as the power consumption of the ultrasonic sensor 27.

[0040] When the ambient environment sensors are cameras, the power consumption of each sensor varies depending on the resolution and the number of image data (number of frames) output per unit time. In this case, the higher the resolution (higher definition) and the greater the number of frames output per unit time, the greater the power consumption. Also, when the ambient environment sensors are LiDAR or millimeter-wave radar, the power consumption of each sensor varies depending on the irradiation density of optical waves or electromagnetic waves and the number of measurement data (point cloud data) generated per unit time (number of frames). In this case, the higher the irradiation density (higher definition) and the greater the number of frames output per unit time, the greater the power consumption.

[0041] The sensor information storage unit 55 also stores coverage information indicating the ratio of the measurement range of one or more surrounding environment sensors to the entire measurement range measured by all surrounding environment sensors. The coverage is calculated for each area obtained by dividing the area around the vehicle 1 into four areas: a front area, a rear area, a right-hand area, and a left-hand area. The coverage may be, for example, one or both of the ratio of the measurable distance of each surrounding environment sensor to the longest measurable distance for each area and the ratio of the measurable angle of each surrounding environment sensor to the maximum measurable angle for each area.

[0042] 6 is an explanatory diagram showing how to calculate the coverage of the measurement ranges of the long-range front camera 11, the short-range front camera 13, and the LiDAR 23, whose main measurement ranges are the forward area. In the forward area, the measurable distance L1 of the long-range front camera 11 corresponds to the longest measurable distance, and the coverage of the measurement ranges of the long-range front camera 11, the short-range front camera 13, and the LiDAR 23 is calculated as the ratio of the measurable distance of each of the long-range front camera 11, the short-range front camera 13, and the LiDAR 23 to the measurable distance L1 of the long-range front camera 11 (L1 / L1, L2 / L1, L3 / L1). In addition, in the forward area, the measurable angle θ3 of the short-range front camera 13 corresponds to the maximum measurable angle, and the coverage rate of the measurement range of the long-range front camera 11, the short-range front camera 13 and the LiDAR 23 is calculated as the ratio of the measurable angle of each of the long-range front camera 11, the short-range front camera 13 and the LiDAR 23 to the measurable angle θ3 of the short-range front camera 13 (θ1 / θ3, θ2 / θ3, θ3 / θ3).

[0043] The sensor information storage unit 55 also stores information on the overlap rate of each overlap area where the measurement ranges of two or more ambient environment sensors overlap. In this embodiment, for each of the forward area, right side area, left side area, and rear area centered on the vehicle 1, the ratio of the area of ​​each overlap area to the area of ​​the entire two-dimensional plane is stored as the overlap rate. The overlap rate of each overlap area is expressed by the following formula: "Area" indicates the area of ​​the two-dimensional plane in the front-rear and left-right directions of the vehicle 1. The overlap rate is calculated for each overlap area. Overlap rate = Area of ​​overlap area / Total area of ​​area

[0044] For example, the overlap rate of the overlap area CA between the measurement range DA3 of the right front camera 15R and the measurement range DA10 of the right side radar 25R shown in Figure 4 is calculated as the ratio of the area of ​​the overlap area CA to the total area of ​​the right side area of ​​the vehicle 1 (see Figure 14 described below).

[0045] (Map Data Storage Unit) The map data storage unit 57 is configured by a storage element such as RAM or ROM connected to the processing unit 51 so as to be able to communicate with it, or a storage medium such as an HDD, CD, DVD, SSD, USB flash, or storage device. The map data includes information on road structure. The information on road structure includes information on road type (such as general roads and expressways), the number of lanes (driving lanes) on the road, merging points, intersections, etc.

[0046] The map data stored in the map data storage unit 57 is configured to be able to identify the position of the vehicle 1 based on the position information detected by the position information sensor 31. For example, the map data is associated with latitude and longitude information, and the processing unit 51 can identify the position of the vehicle 1 on the map data based on the latitude and longitude information of the vehicle 1 detected by the position information sensor 31.

[0047] (1-2-2. Functional Configuration of Processing Unit) Next, the functional configuration of the processing unit 51 of the surrounding environment detection processing device 50 will be described. The processing unit 51 includes an acquisition unit 61, a weight setting processing unit 63, a sensor setting processing unit 65, an object detection processing unit 67, a driving assistance processing unit 69, and a notification processing unit 71. Each of these units is a function realized by execution of a computer program by one or more processors such as a CPU. However, part of the acquisition unit 61, the weight setting processing unit 63, the sensor setting processing unit 65, the object detection processing unit 67, the driving assistance processing unit 69, and the notification processing unit 71 may be configured using analog circuits.

[0048] (Acquisition Unit) The acquisition unit 61 acquires sensor signals output from the surrounding environment sensor and the position information sensor 31. The acquisition unit 61 also acquires information or messages transmitted from the vehicle control unit 41 and the BMS 9.

[0049] (Weight Setting Processing Unit) The weight setting processing unit 63 sets weights for each coverage rate and overlap rate to select one or more ambient environment sensors to be used for detecting the ambient environment, taking into account the coverage rate and overlap rate of the measurement range of each ambient environment sensor. In this embodiment, the weight setting processing unit 63 sets the weights by referring to weight setting information in which weights are set according to the object occupancy rate in the measurement range around the vehicle 1. The weight setting information is stored in advance in the storage unit 53, for example.

[0050] (Sensor Setting Processing Unit) The sensor setting processing unit 65 selects one or more surrounding environment sensors to be used for detecting the surrounding environment using the weights set by the weight setting processing unit 63. In this embodiment, the sensor setting processing unit 65 determines an initial setting for the combination of surrounding environment sensors to be used based on the type of road on which the vehicle 1 is traveling, and then selects the surrounding environment sensors to be used using weights set according to the object occupancy rate.

[0051] The sensor setting processing unit 65 reads the road environment of the traveling position of the vehicle 1 identified by the position information sensor 31 from the map data, and determines an initial setting combination of the surrounding environment sensors for the corresponding road environment. The sensor setting processing unit 65 applies the weights set by the weight setting processing unit 63 to the determined combination of surrounding environment sensors to determine the surrounding environment sensors to be used.

[0052] The sensor setting processor 65 may also set the availability of each ambient environment sensor to be used according to the object occupancy rate. The availability rate refers to the number of frames per unit time for a camera, and the irradiation density of optical or electromagnetic waves or the number of frames per unit time for LiDAR and millimeter-wave radar, which may affect the resolution of the ambient environment sensor. For example, the sensor setting processor 65 may lower the availability rate as the object occupancy rate decreases, thereby reducing the accuracy of the object detection process. This reduces the power consumption of ambient environment sensors that measure areas with a low rate of object presence.

[0053] (Object Detection Processing Unit) The object detection processing unit 67 executes processing to detect objects in each area based on information on the measurement results of the ambient environment sensors determined by the sensor setting processing unit 65. When detecting objects using multiple ambient environment sensors in each area, the object detection processing unit 67 executes processing to detect objects by matching the coordinate systems of the spatial regions measured by each ambient environment sensor and fusing the measurement results. The processing itself to detect objects using each selected ambient environment sensor is executed by a conventionally known method.

[0054] (Driving Assistance Processing Unit) The driving assistance processing unit 69 executes a driving assistance function that automatically controls some or all of the driving operations of the vehicle 1, or temporarily controls the driving operations of the vehicle 1. Examples of driving assistance functions include automatic driving (fully automatic driving) that controls the acceleration / deceleration and steering angle of the vehicle 1 to automatically drive the vehicle 1 to a destination, following control that controls the acceleration / deceleration of the vehicle 1 to make the vehicle 1 follow a preceding vehicle, lane keeping control that controls the steering angle of the vehicle 1 to prevent the vehicle 1 from going out of a boundary line, emergency braking control that generates braking force on the vehicle 1 in an emergency to avoid a collision between the vehicle 1 and an obstacle or to mitigate the impact of a collision, and automatic steering control that controls the steering angle of the vehicle 1 in an emergency to avoid a collision between the vehicle 1 and an obstacle or to mitigate the impact of a collision. However, other driving assistance functions may also be executed. The driving assistance processing unit 69 controls the acceleration / deceleration, braking force, or steering angle of the vehicle 1 based on information about the surrounding environment of the vehicle 1 detected by the object detection processing unit 67, and executes the above-mentioned driving assistance functions.

[0055] (Notification Processing Unit) The notification processing unit 71 drives the notification device 43 to present various information to the driver. For example, the notification processing unit 71 notifies the driver of the presence of an object detected by the object detection processing unit 67. However, the content of the notification by the notification processing unit 71 is not particularly limited.

[0056] 1-3. Object Detection Processing Operation Up to this point, the configuration of the surrounding environment detection processing device 50 according to this embodiment has been described. Next, an example of the operation of the object detection processing by the surrounding environment detection processing device 50 will be specifically described.

[0057] 7 and 8 are flowcharts showing the processing operation of the surrounding environment detection processing device 50. The flowcharts shown in Fig. 7 and 8 are constantly executed, for example, at predetermined processing cycles.

[0058] First, when the processing unit 51 detects that the ignition switch of the vehicle 1 has been turned on (IG=ON) (step S1), the sensor setting processing unit 65 acquires information about the SOC of the high-voltage battery 8 based on a signal output from the BMS 9 and determines whether the SOC is equal to or lower than a predetermined threshold (step S3). The predetermined threshold is a threshold for determining whether the cruising range of the vehicle 1 is short and may be set to any appropriate value. The predetermined threshold may be a fixed value, or may be a variable value that is set depending on the distance to a destination of the vehicle 1 when the destination is set in the navigation system, for example.

[0059] If the sensor setting processing unit 65 does not determine that the SOC of the high-voltage battery 8 is equal to or lower than the predetermined threshold (S3 / No), it selects all the surrounding environment sensors as the surrounding environment sensors to be used (step S5). In this case, the process proceeds to step S25, and the object detection processing unit 67 executes a process of detecting objects around the vehicle 1 based on the measurement information output from all the surrounding environment sensors (step S25).

[0060] On the other hand, if the sensor setting processing unit 65 determines that the SOC of the high-voltage battery 8 is equal to or lower than the predetermined threshold (S3 / Yes), the sensor setting processing unit 65 acquires information about the road environment on which the vehicle 1 is traveling (step S7). For example, the sensor setting processing unit 65 determines the road environment on which the vehicle 1 is traveling based on the position information output from the position information sensor 31 and map data. The sensor setting processing unit 65 may determine the road environment from the environment around the vehicle 1 detected based on measurement information from an operating ambient environment sensor.

[0061] Next, the sensor setting processing unit 65 selects an initial setting for a combination of ambient environment sensors according to the road environment (step S9).

[0062] 9 to 12 show the initial settings for the combination of ambient environment sensors according to road type. Measurement areas surrounded by dashed lines indicate that the corresponding ambient environment sensors will not be used. Note that in this embodiment, all ultrasonic sensors are always in operation and are not included in the selection targets.

[0063] 9 shows the initial settings for the combination of surrounding environment sensors when the vehicle 1 is traveling on a highway. When the vehicle 1 is traveling on a highway, there is a low possibility that objects other than the vehicle are present in the surrounding area. Therefore, the initial setting is set to surrounding environment sensors that can measure long distances while measuring the areas in front of, behind, on both sides of the vehicle 1.

[0064] 10 shows the initial settings for the combination of surrounding environment sensors when the vehicle 1 is traveling on a main road. When the vehicle 1 is traveling on a main road, as with an expressway, there is a low possibility that objects other than the vehicle are present in the surrounding area, so the initial settings are set to surrounding environment sensors that can measure long distances while measuring the areas in front, behind, on both sides of the vehicle 1.

[0065] 11 shows the initial settings of the combination of surrounding environment sensors when the vehicle 1 is traveling on a suburban road. When the vehicle 1 is traveling on a suburban road, the possibility of objects being present in the surrounding area is basically low, so the minimum number of surrounding environment sensors is set as the initial setting.

[0066] 12 shows the initial settings of the combination of surrounding environment sensors when the vehicle 1 is traveling on an urban road. When the vehicle 1 is traveling on an urban road, there is a high possibility that objects are present in the surroundings, and pedestrians, bicycles, etc. may be moving in a complex manner. Therefore, all surrounding environment sensors are set to the initial settings.

[0067] Next, the sensor setting processing unit 65 determines whether there is any change in the road environment (step S11). The sensor setting processing unit 65 determines whether the road environment on which the vehicle 1 is traveling has changed from the road environment determined in step S7. If the sensor setting processing unit 65 determines that there has been a change in the road environment (S11 / No), the sensor setting processing unit 65 returns to step S7, determines the road environment, and changes the combination of ambient environment sensors to the initial setting corresponding to the road environment (step S9).

[0068] On the other hand, if the sensor setting processing unit 65 determines that there is no change in the road environment (S11 / Yes), it starts counting the weight update period (step S13). Next, the sensor setting processing unit 65 determines whether the count of the weight update period started in step S13 is less than a predetermined threshold (step S15). The predetermined threshold may be set to any value as the timing for updating the weight setting, and may be set to 10 seconds, for example.

[0069] Next, the weight setting processing unit 63 performs calculations on elements for setting weights (step S17).

[0070] 13 is a flowchart showing the calculation process of the weight setting elements in this embodiment. The weight setting processing unit 63 acquires information on the object detection results up to the previous processing cycle (step S31). The weight setting processing unit 63 may acquire information on the object detection results calculated in at least the previous processing cycle, but preferably acquires information on the object detection results calculated in the most recent multiple processing cycles. If the information on the object detection results calculated in the most recent multiple processing cycles is available, it becomes possible to calculate the movement direction and movement speed of the detected object.

[0071] Next, the weight setting processing unit 63 calculates the object occupancy rate for each of the front area, right side area, left side area, and rear area based on the acquired information on the object detection results (step S33).

[0072] FIG. 14 shows an example of a method for calculating the object occupancy rate. In the illustrated example, the areas within a predetermined distance on each of the front, rear, left, and right sides of the vehicle 1 are divided vertically into eight equal parts and horizontally into ten equal parts. The object occupancy rate is calculated for each of the forward area, rear area, right side area, and left side area, for example. In the forward area, the object occupancy rate is zero, which is the ratio of the number (0) of mesh areas in which the presence of objects (other vehicles and pedestrians in the illustrated example) has been detected out of the total number (6) of mesh areas. Similarly, the object occupancy rate in the rear area is zero. In the right side area, the object occupancy rate is 12.5%, which is the ratio of the number (4) of mesh areas (indicated by diagonal lines) in which the presence of objects (other vehicles and pedestrians in the illustrated example) has been detected out of the total number (32) of mesh areas. In the left side area, the object occupancy rate is 37.5%, which is the ratio of the number (12) of mesh areas (indicated by diagonal lines) in which the presence of objects (other vehicles and pedestrians in the illustrated example) has been detected out of the total number (32) of mesh areas. The object information used to calculate the object occupancy rate is information on the object detection results up to the previous calculation cycle.

[0073] The range of the area serving as the denominator of the object occupancy rate and the number of dividing meshes are not limited to the example shown in the figure, and may be set arbitrarily. Furthermore, the number of divided areas is not limited to four, and for example, the right side area may be further divided into a right front side area and a right rear side area. Furthermore, the types of objects whose presence is detected are not limited to moving objects such as vehicles and pedestrians, but also include stationary objects such as buildings and natural objects.

[0074] Next, the weight setting processing unit 63 refers to the weight setting information according to the object occupancy rate, and acquires the information of the weight according to the calculated object occupancy rate (step S35).

[0075] 15 shows an example of weight setting information set according to the object occupancy rate. In the example shown, the object occupancy rate is divided into 10% increments, and weights are set for the coverage rate and overlap rate for each of the forward area, right side area, left side area, and rear area for each object occupancy rate. The weights are set within a range from 0 to 1.0. With regard to coverage rate, the weight for the forward area is set to 1.0 regardless of the object occupancy rate because object detection is of high importance for the forward area. The weights for the other coverage rates and overlap rates are set to larger values ​​as the object occupancy rate increases.

[0076] Returning to Figure 8, the weight setting processing unit 63 calculates the elements for setting weights according to the object occupancy rate in step S17, and then sets weights according to the object occupancy rate for each of the forward area, rear area, right side area, and left side area (step S19).

[0077] 14, the object occupancy rates of the front area, right side area, left side area, and rear area are 0%, 12.5%, 37.5%, and 0%, respectively, and the coverage weight of the front area is set to 1.0, the coverage weight of the front side area to 0.3, the coverage weight of the left side area to 0.5, and the coverage weight of the rear area to 0.3. Also, the overlap rate weight of the front area is set to 0.2, the overlap rate weight of the right side area to 0.2, the overlap rate weight of the left side area to 0.3, and the overlap rate weight of the rear area to 0.2.

[0078] Next, the sensor setting processor 65 determines a combination of ambient environment sensors to use based on the set weights (step S21). The sensor setting processor 65 selects the ambient environment sensors to use from the initial setting of the combination of ambient environment sensors already determined in step S9, using weights set according to the object occupancy. This allows for coordination between the power consumption of the ambient environment sensors and the need for object detection when the SOC of the high-voltage battery 8 is low.

[0079] For example, while the vehicle 1 is traveling on an urban road, the initial combination of ambient environment sensors to be used is the combination shown in Figure 12. When the vehicle 1 is placed in the situation shown in Figure 14, the selection process for the ambient environment sensor to detect an object in the right-side area is performed as follows. Because the coverage weight is 0.3 when the object occupancy rate in the right-side area is 12.5%, the sensor setting processor 65 selects one or more ambient environment sensors that can ensure a measurement angle of approximately 60 degrees, which is calculated by multiplying the maximum measurement angle (= 180 degrees) in the right-side area by 0.3. When the measurable angles of the right front camera 15R, the right rear camera 17R, and the right-side forward radar 25R are 60 degrees or greater, the sensor setting processor 65 selects the right front camera 15R, the right rear camera 17R, and the right-side forward radar 25R as candidates, respectively.

[0080] Furthermore, since the weight of the overlap rate is 0.2 when the object occupancy rate in the right-side area is 12.5%, the sensor setting processing unit 65 selects as candidates a plurality of surrounding environment sensors that can secure a measurement range of 3.0%, which is calculated by multiplying the total overlapping area (e.g., 15%) in the right-side area by 0.2. For example, if the overlapping area between the measurement range DA3 of the right front camera 15R and the measurement range DA10 of the right-side side radar 25R, and the overlapping area between the measurement range DA5 of the right rear camera 17R and the measurement range DA10 of the right-side side radar 25R are each 3.0% or more, the sensor setting processing unit 65 selects as candidates the right front camera 15R and the right-side side radar 25R, or the right rear camera 17R and the right-side side radar 25R, respectively.

[0081] Furthermore, the sensor setting processing unit 65 compares the candidates selected based on the coverage rate with the candidates selected based on the overlap rate, and selects the right front camera 15R, the right rear camera 17R, and the right side radar 25R as candidates for the surrounding environment sensors to be used, in order to reduce the power consumption of the surrounding environment sensors that measure the right side area. Through the processing up to this point, the candidates for the surrounding environment sensors to be used are determined.

[0082] Then, the sensor setting processing unit 65 determines the surrounding environment sensor to be used from among the candidate surrounding environment sensors, taking into consideration the position of the object detected up to the previous processing cycle. In the example shown in Fig. 14, since another vehicle is detected to the right front of the vehicle 1, the sensor setting processing unit 65 determines, as the surrounding environment sensor to be used, the right front camera 15R, the right rear camera 17R, and the right side radar 25R, which are the candidate surrounding environment sensors to be used, as the surrounding environment sensor to be used, since the measurement range is directed in the direction in which the object is detected.

[0083] Similarly, for the other forward area, left side area, and rear area, the sensor setting processing unit 65 selects candidate ambient environment sensors based on a weight of coverage set according to the object occupancy rate and candidate ambient environment sensors based on a weight of overlap rate, and determines the candidate ambient environment sensors and the number of candidate ambient environment sensors that will reduce power consumption. In addition, the sensor setting processing unit 65 determines the ambient environment sensors to be used for object detection in each of the forward area, left side area, and rear area, taking into account the positions of objects detected up to the previous processing cycle.

[0084] Next, the object detection processing unit 67 executes a process of detecting objects in each area based on the information on the measurement results of the surrounding environment sensors determined by the sensor setting processing unit 65 (step S23). The information on the object detection results is used for the driving assistance process and the notification process. After determining the combination of surrounding environment sensors to be used, the sensor setting processing unit 65 may further set the operation rate of each surrounding environment sensor to be used according to the object occupancy rate. This makes it possible to further reduce the power consumption of surrounding environment sensors that measure areas with a low rate of object presence.

[0085] Next, the processing unit 51 determines whether the ignition switch of the vehicle 1 is turned off (IG=OFF) (step S25). If the processing unit 51 does not determine that the ignition switch of the vehicle 1 is turned off (S25 / No), the processing unit 51 returns to step S11 and repeats the processing of each step described above. On the other hand, if the processing unit 51 determines that the ignition switch of the vehicle 1 is turned off (S25 / Yes), the processing unit 51 ends the object detection processing operation.

[0086] <1-4. Effects> As described above, the surrounding environment detection processing device 50 according to this embodiment sets weights for the coverage rate and overlap rate of the measurement ranges of the multiple surrounding environment sensors in accordance with the object occupancy rate around the vehicle 1, which is one of the driving environments of the vehicle 1, and uses the weights to select one or more surrounding environment sensors to use for detecting the surrounding environment. This reduces the power consumption required for object detection processing in driving environments where there are few objects around the vehicle 1, and makes it possible to suppress a decrease in the cruising range of the drive motor 2 while coordinating the power consumption of the surrounding environment sensors with the need for object detection.

[0087] The surrounding environment detection processing device 50 according to this embodiment selects the surrounding environment sensor in accordance with the object occupancy rate when the SOC of the high-voltage battery 8 is low, thereby extending the cruising distance of the vehicle 1 after the SOC of the high-voltage battery 8 is low.

[0088] Furthermore, the surrounding environment detection processing device 50 according to this embodiment selects a combination of surrounding environment sensors that consumes less power from among candidate combinations of surrounding environment sensors selected from the viewpoint of the overlap rate of the measurement ranges of the multiple surrounding environment sensors and candidate combinations of surrounding environment sensors selected from the viewpoint of the coverage rate of the measurement ranges of the multiple surrounding environment sensors. This reduces the power consumption required for object detection processing and enables the minimum amount of object detection processing to be performed.

[0089] Furthermore, the surrounding environment detection processing device 50 according to this embodiment may change the operating rate of the surrounding environment sensors in operation according to the object occupancy rate around the vehicle 1. This makes it possible to further reduce the power consumption required for the object detection process and to perform the minimum amount of object detection process.

[0090] <<2. Second Embodiment>> Next, a surrounding environment detection processing device according to a second embodiment of the present disclosure will be described. The surrounding environment detection processing device according to the first embodiment sets weights for the coverage rate and the overlap rate according to the object occupancy rate in the measurement range around the vehicle, and determines the combination of surrounding environment sensors to be used. In contrast, the surrounding environment detection processing device according to the second embodiment sets weights for the coverage rate and the overlap rate based on information regarding the occurrence of an accident on the vehicle's driving route or planned driving route, and determines the combination of surrounding environment sensors to be used.

[0091] The surrounding environment detection processing device according to this embodiment has the same configuration as the surrounding environment detection processing device according to the first embodiment, except that the weight setting processing by the weight setting processing unit 63 is different from that of the surrounding environment detection processing device according to the first embodiment. Below, the surrounding environment detection processing device according to this embodiment will be described in terms of the differences from the surrounding environment detection processing device according to the first embodiment.

[0092] The map data stored in the map data storage unit 57 of the surrounding environment detection processing device 50 according to this embodiment includes information on accident locations recorded in association with information on the frequency of traffic accidents and the type of accident. The accident locations may be specific locations or may be sections divided by predetermined criteria such as distance. The information on the frequency of traffic accidents is classified, for example, as "frequent," "average," or "rare" based on past statistical data. The information on the type of accident is classified, for example, as "collision from the subject vehicle (rear-end collision of the subject vehicle)," "left-side collision," or "right-side collision." The information on the accident locations recorded in association with information on the frequency of traffic accidents and the type of accident may be acquired from an external server or the like communicatively connected to the surrounding environment detection processing device 50 via wireless communication means.

[0093] 16 is a flowchart showing the calculation process of elements for setting weights by the weight setting processing unit 63 of the surrounding environment detection processing device 50 according to this embodiment. The weight setting processing unit 63 acquires information on the traveling position of the vehicle 1 based on the position information of the vehicle 1 output from the position information sensor 31 and map data (step S41). Next, the weight setting processing unit 63 acquires information on the frequency of traffic accidents and the types of accidents at the traveling point corresponding to the acquired traveling position (step S43).

[0094] Next, the weight setting processing unit 63 refers to the weight setting information according to the frequency of traffic accidents and the type of accident, and obtains weight information according to the number of traffic accidents and the type of accident at the traveling point of the vehicle 1 (step S45).

[0095] FIG. 17 shows an example of weight setting information set according to the frequency of accidents and the type of accidents. In the example shown, weights for the coverage rate and overlap rate are set for each of "high," "normal," and "low" indicating the frequency of accidents. The weights are set within a range from 0 to 1.0. The weights for the coverage rate and overlap rate are set to larger values ​​as the frequency of accidents increases. In addition, weights for the coverage rate and overlap rate are set for each of "rear-end collision of own vehicle," "left-side collision," and "right-side collision," indicating the type of accident. The weights for the coverage rate and overlap rate have different set values ​​depending on whether the collision is from the own vehicle or the driver's side of the own vehicle.

[0096] After acquiring information on the weights according to the frequency of accidents and the types of accidents, the weight setting processing unit 63 sets weights according to the frequency of accidents and the types of accidents for each of the front area, rear area, right side area, and left side area (step S19 in FIG. 8). For example, the weight setting processing unit 63 sets a weight for each of the front area, rear area, right side area, and left side area by selecting the larger of the weights according to the frequency of accidents and the types of accidents.

[0097] Processing operations other than those described above may be executed in the same manner as in the surrounding environment detection processing device 50 according to the first embodiment. The surrounding environment detection processing device 50 according to this embodiment sets weights for the coverage and overlap rates of the measurement ranges of the multiple surrounding environment sensors in accordance with information regarding the occurrence of an accident on the driving route or planned driving route of the vehicle 1, which is one of the driving environments of the vehicle 1, and selects one or more surrounding environment sensors to use for detecting the surrounding environment using the weights. This reduces the power consumption required for object detection processing in driving environments where the possibility of traffic accidents is low, and makes it possible to suppress a decrease in the cruising range of the drive motor 2 while coordinating the power consumption of the surrounding environment sensors with the need for object detection.

[0098] 3. Third embodiment Next, a surrounding environment detection processing device according to a third embodiment of the present disclosure will be described. The surrounding environment detection processing device according to the third embodiment sets weights for the coverage rate and the overlap rate based on information on a blind spot occupancy rate, which is the proportion of a blind spot area seen from the vehicle within a predetermined range around the vehicle, and determines a combination of surrounding environment sensors to be used.

[0099] The surrounding environment detection processing device according to this embodiment has the same configuration as the surrounding environment detection processing device according to the first embodiment, except that the weight setting processing by the weight setting processing unit 63 is different from that of the surrounding environment detection processing device according to the first embodiment. Below, the surrounding environment detection processing device according to this embodiment will be described in terms of the differences from the surrounding environment detection processing device according to the first embodiment.

[0100] 18 shows a flowchart of the calculation process of elements for setting weights by the weight setting processor 63 of the surrounding environment detection processing device 50 according to this embodiment. The weight setting processor 63 acquires information on object detection results up to the previous processing cycle (step S51). As in step S31 described above, the weight setting processor 63 may acquire information on object detection results calculated at least in the previous processing cycle, but preferably acquires information on object detection results calculated in the most recent multiple processing cycles.

[0101] Next, the weight setting processing unit 63 calculates the blind spot occupancy rate for each of the forward area, right side area, left side area, and rear area based on the acquired information on the object detection result (step S53).

[0102] FIG. 19 shows an example of a method for calculating the blind spot occupancy rate. In the illustrated example, the areas within a predetermined distance on each of the front, rear, left, and right sides of the vehicle 1 are divided vertically into eight equal parts and horizontally into ten equal parts. The blind spot occupancy rate is calculated for each of the forward area, rear area, right side area, and left side area, for example. In the forward area, the blind spot occupancy rate is zero, which is the ratio of the number of mesh areas (0) located further back than the mesh area where the presence of an object (another vehicle and a pedestrian in the illustrated example) has been detected out of the total number of mesh areas (6). Similarly, the blind spot occupancy rate in the rear area is zero. In the right side area, the blind spot occupancy rate is approximately 21.88, which is the ratio of the number of mesh areas (7) located further back than the mesh area (indicated by diagonal lines) where the presence of an object (another vehicle and a pedestrian in the illustrated example) has been detected out of the total number of mesh areas (32). In the left side area, the blind spot occupancy rate, which is the percentage of the number (8) of mesh areas (areas indicated by grid lines) located further back than the mesh area (area indicated by diagonal lines) where the presence of objects (other vehicles and pedestrians in the illustrated example) has been detected out of the total number (32) of mesh areas, is 25.0%. The information on the objects producing the blind spot, which is the basis for calculating the blind spot occupancy rate, uses information on the object detection results up to the previous calculation cycle.

[0103] The range of the area that is the denominator of the blind spot occupancy rate and the number of dividing meshes are not limited to the example shown in the figure and may be set arbitrarily. Furthermore, the number of area divisions is not limited to four. For example, the right side area may be further divided into a right front side area and a right rear side area. Furthermore, the types of objects that create blind spots are not limited to moving objects such as vehicles and pedestrians, but also include stationary objects such as buildings and natural objects.

[0104] Next, the weight setting processing unit 63 refers to the weight setting information according to the blind spot occupancy rate, and acquires the weight information according to the calculated blind spot occupancy rate (step S55).

[0105] 20 shows an example of weight setting information set according to the blind spot occupancy rate. In the illustrated example, the blind spot occupancy rate is divided into 10% increments, and weights are set for the coverage rate and overlap rate of the front area, right side area, left side area, and rear area for each blind spot occupancy rate. The weights are set within a range from 0 to 1.0. Regarding coverage rate, the weight of the front area is set to 1.0 regardless of the blind spot occupancy rate because object detection is of high importance in the front area. The weights of the other coverage rates and overlap rates are set to larger values ​​as the blind spot occupancy rate increases.

[0106] The processing operations other than those described above may be performed in the same manner as in the surrounding environment detection processing device 50 according to the first embodiment. The surrounding environment detection processing device 50 according to this embodiment sets weights for the coverage rate and overlap rate of the measurement ranges of the multiple surrounding environment sensors according to the blind spot occupancy rate around the vehicle 1, which is one of the driving environments of the vehicle 1, and selects one or more surrounding environment sensors to be used for detecting the surrounding environment using the weights. As a result, in a driving environment with few blind spots from the vehicle 1, the power consumption required for object detection processing is reduced, and a decrease in the cruising distance of the drive motor 2 can be suppressed while coordinating the power consumption of the surrounding environment sensors with the need for object detection. Conversely, in a driving environment with many blind spots from the vehicle 1, the surrounding environment sensors for detecting objects can be multiplexed, ensuring the need for object detection.

[0107] 4. Fourth Embodiment Next, a surrounding environment detection processing device according to a fourth embodiment of the present disclosure will be described. The surrounding environment detection processing device according to the fourth embodiment sets weights for the coverage rate and the overlap rate based on information on the types of objects present around the vehicle and the number of types of objects, and determines a combination of surrounding environment sensors to be used.

[0108] The surrounding environment detection processing device according to this embodiment has the same configuration as the surrounding environment detection processing device according to the first embodiment, except that the weight setting processing by the weight setting processing unit 63 is different from that of the surrounding environment detection processing device according to the first embodiment. Below, the surrounding environment detection processing device according to this embodiment will be described in terms of the differences from the surrounding environment detection processing device according to the first embodiment.

[0109] 21 shows a flowchart of the calculation process of elements for setting weights by the weight setting processor 63 of the surrounding environment detection processing device 50 according to this embodiment. The weight setting processor 63 acquires information on object detection results up to the previous processing cycle (step S61). As in step S31 described above, the weight setting processor 63 may acquire information on object detection results calculated at least in the previous processing cycle, but preferably acquires information on object detection results calculated in the most recent multiple processing cycles.

[0110] Next, the weight setting processing unit 63 determines the type and number of types of objects around the vehicle 1 based on the acquired information (step S63). The acquired information on the object detection result includes information on the type of object identified by pattern matching processing or the like, and the weight setting processing unit 63 determines the type and number of types of objects around the vehicle 1 from this information.

[0111] Next, the weight setting processing unit 63 refers to weight setting information according to the type of object around the vehicle 1 and weight setting information according to the number of types of object, and obtains weight information according to the type of object and the number of types of object (step S65).

[0112] FIG. 22 shows an example of weight setting information set according to the type of object and the number of types of object. In the illustrated example, "passenger car," "pedestrian," "bicycle," "taxi," "truck," and "motorcycle" are set as object types, and weights for the coverage rate and overlap rate of each area are set for each of them. The weights are set within a range from 0 to 1.0. The weights for the coverage rate and overlap rate are set to larger values ​​as the damage that may occur to at least one of the host vehicle and the other vehicle in the event of a collision increases. Furthermore, the weights for the coverage rate and overlap rate of each area are set according to the number of types of object. Considering that the more types of objects there are, the more difficult it is to predict the movement of each object, the larger the weights for the coverage rate and overlap rate are set to.

[0113] After acquiring information on the weights according to the types of objects and the number of types of objects around the vehicle 1, the weight setting processing unit 63 sets weights according to the types of objects and the number of types of objects for each of the forward area, rear area, right side area, and left side area (step S19 in FIG. 8 ). For example, the weight setting processing unit 63 sets a weight for each of the forward area, rear area, right side area, and left side area by selecting the larger of the weight according to the type of object and the weight according to the number of types of objects.

[0114] The processing operations other than those described above may be performed in the same manner as in the surrounding environment detection processing device 50 according to the first embodiment. The surrounding environment detection processing device 50 according to this embodiment sets weights for the coverage and overlap rates of the measurement ranges of the multiple surrounding environment sensors in accordance with weight information corresponding to the types and number of types of objects present around the vehicle 1, which is one of the driving environments of the vehicle 1, and selects one or more surrounding environment sensors to use for detecting the surrounding environment using the weights. This reduces the power consumption required for object detection processing in driving environments where the movement of surrounding objects is relatively easy to predict and damage in the event of a collision is expected to be small, making it possible to suppress a decrease in the cruising range of the drive motor 2 while coordinating the power consumption of the surrounding environment sensors with the need for object detection.

[0115] Although the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art to which the present disclosure pertains can conceive of various modifications or alterations within the scope of the technical ideas set forth in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure.

[0116] For example, in the above-described embodiments, the weights of the coverage rate and overlap rate of each area are determined based on factors for setting different weights, and a combination of ambient environment sensors to be used is selected, but the technology of the present disclosure is not limited to such an example. The weights of the coverage rate and overlap rate of each area may be determined by arbitrating at least two of the coverage rates and overlap rates determined based on factors for setting weights used in the above-described embodiments.

[0117] FIG. 23 is a flowchart showing an example of determining the weights for the coverage and overlap rates of each area by arbitrating all of the coverage rates and overlap rates determined based on the factors used to set the weights in the above-described embodiments. The weight setting processor 63 acquires information on the coverage and overlap rates of each area according to the flowcharts shown in FIGS. 13, 16, 18, and 21 (steps S71 to S77). The weight setting processor 63 then selects the largest weight for each coverage and overlap rate and sets it as the weight for the coverage and overlap rate of each area. This allows for balancing the need for object detection based on various factors with the power consumption of the surrounding environment sensors while suppressing a decrease in the driving range of the drive motor 2.

[0118] In addition, in the above embodiment, the processing to assist vehicle driving was performed by the surrounding environment detection processing device installed in the vehicle 1, but some or all of the functions may be possessed by an external management server.

[0119] In addition, the technology of the present disclosure can also be realized as a vehicle equipped with the surrounding environment detection processing device described in the above embodiment, a surrounding environment detection processing method using the surrounding environment detection processing device, a computer program that causes a computer to function as the above-mentioned driving assistance system, and a non-transitory tangible recording medium on which the computer program is recorded.

[0120] 1: Vehicle 8: High-voltage battery 11: Long-range front camera 13: Short-range front camera 15L: Left front camera 15R: Right front camera 17L: Left rear camera 17R: Right rear camera 19: Long-range rear camera 21: Short-range rear camera 25L: Left side radar 25R: Right side radar 27: Ultrasonic sensor 31: Position information sensor 33: Vehicle state sensor 39: Low-voltage battery 50: Surrounding environment detection processing device 51: Processing unit 53: Memory unit 55: Sensor information memory unit 57: Map data memory unit 61: Acquisition unit 63: Weight setting processing unit 65: Sensor setting processing unit 67: Object detection processing unit 69: Driving assistance processing unit 71: Notification processing unit

Claims

1. A surrounding environment detection processing device that detects the surrounding environment of a vehicle based on measurement information from multiple surrounding environment sensors with different measurement ranges, comprising a memory unit that records information on the measurement ranges of each of the surrounding environment sensors, information on a coverage rate that indicates the proportion of the measurement range of one or more of the surrounding environment sensors to the total measurement range measured by all of the surrounding environment sensors, and information on an overlap rate, which is the rate at which the measurement ranges of two or more of the surrounding environment sensors overlap with each other, and sets weights for each of the coverage rate and the overlap rate according to the driving environment of the vehicle, and uses the weights to select one or more of the surrounding environment sensors to use for detecting the surrounding environment.

2. The surrounding environment detection processing device according to claim 1, wherein the information on the vehicle's driving environment used to set the weights includes information on the object occupancy rate, which is the proportion of the area in a predetermined range around the vehicle where objects exist.

3. The surrounding environment detection processing device according to claim 1, wherein the information on the vehicle's driving environment used to set the weight includes information on the occurrence of an accident on the vehicle's driving route or planned driving route.

4. The surrounding environment detection processing device according to claim 1, wherein the information on the vehicle's driving environment used to set the weights includes information on the blind spot occupancy rate, which is the proportion of blind spot areas seen from the vehicle within a specified range of areas around the vehicle.

5. The surrounding environment detection processing device according to claim 1, wherein the information on the vehicle's driving environment used to set the weights includes information on the types of objects present around the vehicle and the number of types of the objects.

6. A surrounding environment detection processing method for detecting the surrounding environment of a vehicle based on measurement information from multiple surrounding environment sensors with different measurement ranges, wherein a computer performs the following steps: referring to information on the measurement range of each of the surrounding environment sensors, information on coverage indicating the ratio of the measurement range of one or more of the surrounding environment sensors to the total measurement range measured by all of the surrounding environment sensors, and information on the overlap rate at which the measurement ranges of two or more of the surrounding environment sensors overlap with each other, and setting weights for the coverage rate and the overlap rate according to the driving environment of the vehicle; and using the weights to select one or more of the surrounding environment sensors to use for detecting the surrounding environment.

7. A non-transitory tangible recording medium having recorded thereon a program that causes a computer to perform the following: referencing information on the measurement ranges of multiple ambient environment sensors with different measurement ranges, information on coverage indicating the ratio of the measurement range of one or more of the ambient environment sensors to the total measurement range measured by all of the ambient environment sensors, and information on the overlap rate at which the measurement ranges of two or more of the ambient environment sensors overlap with each other, and setting weights for the coverage rate and the overlap rate according to the driving environment of the vehicle; and using the weights to select one or more of the ambient environment sensors to use for detecting the ambient environment.

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