WO2018198769A1

WO2018198769A1 - Surrounding environment recognition device, display control device

Info

Publication number: WO2018198769A1
Application number: PCT/JP2018/015182
Authority: WO
Inventors: 勇樹堀田; 茂規早瀬; 工藤　真
Original assignee: 日立オートモティブシステムズ株式会社
Priority date: 2017-04-26
Filing date: 2018-04-11
Publication date: 2018-11-01
Also published as: JP2018185668A; JP6838769B2

Abstract

This surrounding environment recognition device, which is installed in a vehicle and recognizes the environment surrounding the vehicle, is equipped with: a host-vehicle information acquisition unit which acquires host-vehicle information pertaining to the movement of the vehicle, including the traveling speed of the vehicle; a surrounding environment element acquisition unit which acquires surrounding environment element information about the environmental elements in the surroundings of the vehicle; and a travel risk determination unit which determines, on the basis of the host-vehicle information and the surrounding environment element information, the travel risk at each of a plurality of positions surrounding the vehicle, wherein the intervals between the plurality of positions in the front-to-rear direction of the vehicle change in accordance with the traveling speed of the vehicle.

Description

Ambient environment recognition device, display control device

The present invention relates to a surrounding environment recognition device and a display control device.

Conventionally, there has been proposed an apparatus that calculates the degree of danger to the traveling of the host vehicle caused by various obstacles existing around the host vehicle and performs driving support according to the calculated degree of risk. With regard to such an apparatus, in Patent Document 1 below, the risk potential of the subject vehicle calculated based on the predicted travel range of the subject vehicle and the risk potential of the subject calculated based on the predicted motion range of the subject are described. A technique for generating a risk potential map that represents the risk of collision between the two for each position based on the overlap is disclosed.

Japanese Unexamined Patent Publication No. 2011-253302

The risk potential map expresses the degree of risk with a fine granularity (high accuracy) when driving at low speeds, while it is necessary to express a wide range of risks when driving at high speeds in order to judge the safety of the host vehicle. There is a need. In the above-mentioned patent document 1, since the interval between the risk calculation points in the risk potential map is set to be fixed, an attempt is made to obtain the risk necessary for the safety judgment for both high speed driving and low speed driving. A wide range of risks must be determined with a fine granularity. As a result, there is a problem that the number of risk calculation points becomes enormous, and the amount of calculation and memory consumption of the apparatus increase dramatically.

A surrounding environment recognition device according to a first aspect of the present invention is mounted on a vehicle, recognizes the surrounding environment of the vehicle, and acquires own vehicle information related to the movement of the vehicle including the traveling speed of the vehicle. Based on the own vehicle information acquisition unit, the surrounding environment element acquisition unit for acquiring the surrounding environment element information for the surrounding environment elements of the vehicle, and the vehicle information and the surrounding environment element information, a plurality of surroundings of the vehicle A travel risk level determining unit that determines a travel risk level at each position, and an interval between the plurality of positions in the front-rear direction of the vehicle changes according to a travel speed of the vehicle.
A display control device according to a second aspect of the present invention displays information related to the vehicle on a display device mounted on the vehicle, and displays travel risk levels at a plurality of positions around the vehicle. A travel risk level map acquisition unit that acquires the travel risk level map, and a travel risk level map display control unit that displays the travel risk level map acquired by the travel risk level map acquisition unit on the display device. The display target range of the travel risk map around the vehicle changes according to the travel speed of the vehicle.

According to the present invention, it is possible to obtain the degree of risk necessary for the safety judgment while suppressing the calculation amount and the memory consumption amount at both high speed running and low speed running.

It is a functional block diagram showing an example of composition of a run control system concerning one embodiment of the present invention. It is a figure which shows an example of a driving | running | working risk map. It is a figure which shows an example of the flowchart of a surrounding environment recognition process. It is a figure which shows an example of the graph which showed the relationship between the travel speed of a vehicle, and the cell length of a travel risk map. It is a figure which shows an example of the graph which showed the relationship between the running speed of a vehicle, the length of the front-back direction of a driving | running | working risk map, and the number of cells. It is a figure which shows an example of the flowchart of the own vehicle existing time range determination process. It is a figure which shows an example of an existing time range map. It is a figure which shows an example of the flowchart of an environmental element presence time range determination process. It is a figure which shows an example of the driving road environment of a vehicle. It is a figure which shows an example of the calculation result of a driving | running | working risk degree map. It is explanatory drawing of an example of the data format of a driving | running | working risk map. It is a figure which shows an example of the flowchart of a driving | running | working risk degree map display process. It is a figure which shows the example of a display screen. It is a figure which shows the example of the display screen at the time of expressing with a distance scale and a time scale, respectively.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a functional block diagram showing an example of the configuration of a travel control system 1 according to an embodiment of the present invention. The travel control system 1 according to the present embodiment is mounted on a vehicle 2 and recognizes current and future risks in traveling of the vehicle 2 after recognizing the situation of obstacles such as a traveling road and surrounding vehicles around the vehicle 2. It is a system for judging and performing appropriate driving support and traveling control. As shown in FIG. 1, the travel control system 1 includes a surrounding environment recognition device 10, an in-vehicle display control device 20, a host vehicle position determination device 30, an external sensor group 40, a vehicle sensor group 50, a map information management device 60, a travel A control device 70, an actuator group 80, a display device 90, and the like are included.

The surrounding environment recognition device 10 is, for example, an ECU (Electronic Control Unit) mounted on the vehicle 2, and includes a processing unit 100, a storage unit 120, and a communication unit 130. In addition, there is no restriction | limiting in particular in the form of the surrounding environment recognition apparatus 10, You may use things other than ECU as the surrounding environment recognition apparatus 10. FIG. For example, the surrounding environment recognition device 10 may be integrated into the travel control device 70, the external sensor group 40, and the like.

The processing unit 100 includes, for example, a memory such as a CPU (Central Processing Unit) and a RAM (Random Access Memory). The processing unit 100 includes a host vehicle information acquisition unit 101, a surrounding environment element acquisition unit 102, an environment element movement prediction unit 103, an existing time range determination unit 104, a travel risk as a part for realizing the functions of the surrounding environment recognition device 10. A degree determination unit 105, a travel risk level map creation unit 106, and a travel risk level map provision unit 107. The processing unit 100 executes processing corresponding to each unit by executing a predetermined operation program stored in the storage unit 120.

The own vehicle information acquisition unit 101 includes, as the own vehicle information related to the movement of the vehicle 2, for example, the position of the vehicle 2, the traveling speed, the steering angle, the operation amount of the accelerator, the operation amount of the brake, the control plan of the vehicle 2 Information such as a plan for controlling the vehicle 2 with such a trajectory and speed) is acquired from the own vehicle position determination device 30, the vehicle sensor group 50, the travel control device 70, the actuator group 80, and the like. The vehicle information acquired by the vehicle information acquisition unit 101 is stored in the storage unit 120 as the vehicle information data group 121.

The surrounding environment element acquisition unit 102, as surrounding environment element information regarding various environment elements around the vehicle 2, for example, information on obstacles existing around the vehicle 2, features indicating road features around the vehicle 2, etc. Is acquired from the outside world sensor group 40 and the map information management device 60. The obstacle existing around the vehicle 2 is, for example, other vehicles moving around the vehicle 2, such as moving vehicles such as bicycles and pedestrians, and parked stationary on the road around the vehicle 2. Vehicles, fallen objects, installations, etc. The surrounding environment element information acquired by the surrounding environment element acquisition unit 102 is stored in the storage unit 120 as the surrounding environment element information data group 122.

The environment element movement prediction unit 103 is based on the surrounding environment element information data group 122 stored in the storage unit 120, and is a moving body such as another vehicle, bicycle, or pedestrian included in the environment element detected by the external sensor group 40. Predict how it will move in the future. The movement prediction result of the moving body by the environment element movement prediction unit 103 is added to the surrounding environment element information corresponding to the moving body, and is stored in the storage unit 120 as the surrounding environment element information data group 122.

The existence time range determination unit 104 is configured to determine a predetermined position around the vehicle 2 based on the own vehicle information data group 121 stored in the storage unit 120 and the movement prediction result of the moving object by the environment element movement prediction unit 103. A time range in which the vehicle 2 and environmental elements can exist is determined. In the following description, the vehicle 2 and the environmental element existing time range determined by the existing time range determining unit 104 are referred to as the own vehicle existing time range and the environmental element existing time range, respectively. The own vehicle existing time range and the environmental element existing time range determined by the existing time range determining unit 104 are added to the own vehicle information and the surrounding environment element information, respectively, and the own vehicle information data group 121, the surrounding environment element information data Each group 122 is stored in the storage unit 120.

The travel risk determination unit 105 includes various parameters represented by the parameter data group 123 stored in the storage unit 120, vehicle information and surrounding environment element information represented by the vehicle information data group 121 and the surrounding environment element information data group 122, respectively. Based on the above, the travel risk around the vehicle 2 is determined.

The travel risk level map creation unit 106 creates a travel risk level map that represents the relationship between each position around the vehicle 2 and the travel risk level based on the travel risk level determination result by the travel risk level determination unit 105. Information related to the travel risk map created by the travel risk map creating unit 106 is stored in the storage unit 120 as the travel risk map data group 124.

The travel risk map providing unit 107 provides information related to the travel risk map of the vehicle 2 based on the travel risk map data group 124 stored in the storage unit 120, other functions in the surrounding environment recognition device 10, This is provided to devices other than the surrounding environment recognition device 10 mounted on the vehicle 2.

The storage unit 120 includes, for example, a storage device such as an HDD (Hard Disk Drive), flash memory, ROM (Read Only Memory), and a memory such as a RAM (Random Access Memory). The storage unit 120 stores a program executed by the processing unit 100, a data group necessary for realizing the system, and the like. In the present embodiment, the vehicle information data group 121, the surrounding environment element information data group 122, the parameter data group 123, and the travel risk map data group 124 are particularly used as information for realizing the function of the surrounding environment recognition device 10. Is stored in the storage unit 120.

The own vehicle information data group 121 is a collection of data related to the vehicle 2. For example, the vehicle information data group 121 includes information on the position of the vehicle 2 acquired from the vehicle position determination device 30 and the state of the vehicle 2 acquired from the vehicle sensor group 50. In addition, the vehicle information data group 121 also includes a time range in which the vehicle 2 can exist at the position around the vehicle 2, that is, information related to the vehicle existence time range described above.

The surrounding environment element information data group 122 is a collection of data related to the surrounding environment of the vehicle 2. For example, digital road map data related to roads around the vehicle 2 acquired from the map information management device 60, recognition data of various environmental elements around the vehicle 2 acquired from the external sensor group 40, and these are integrated and generated. The surrounding environment element information data group 122 is included in the data. Data indicating the movement prediction result of the moving body by the environment element movement prediction unit 103 is also included in the surrounding environment element information data group 122. Furthermore, the surrounding environment element information data group 122 also includes information on a time range in which the environmental element can exist at each position around the vehicle 2, that is, the above-described environment element existence time range. In the surrounding environment element information data group 122, the above data is set for each of a plurality of environment elements. Here, “environmental element” means an information element that affects the traveling of the vehicle 2. For example, other vehicles in the vicinity of the vehicle 2, obstacles such as moving objects such as pedestrians and falling objects, road shapes such as lane and road boundary information, speed regulations, traffic rules such as one-way traffic and traffic lights, etc. The element is included in the “environment element” described above. Although these information elements have various properties, they all have a common point that they give meaning to a position or region in the space around the vehicle 2. Therefore, in the present embodiment, these information elements are handled as “environment elements” in a common framework, and are set as data accumulation targets in the surrounding environment element information data group 122.

Note that “time” in the present embodiment is indicated in a time system based on a certain reference time point. Preferably, the vehicle 2 and the environmental element at each position around the current position of the vehicle 2 with the present time as the reference time point are determined in which time zone in the future (for example, 2 seconds to 3 seconds later). It can be indicated by the vehicle existence time range or the environmental element existence time range. Here, the above “time range” does not necessarily have a wide time, and a specific time point may be set as the own vehicle existing time range or the environmental element existing time range. Also, the probability distribution of the time when the vehicle 2 and the environmental element exist at each position around the current position of the vehicle 2, that is, the distribution of the existence probability of the vehicle 2 and the environmental element at each predetermined time interval at each position It may be shown as an existing time range or an environmental element existing time range.

The parameter data group 123 is a collection of data relating to parameters used by the travel risk map creating unit 106 in creating the travel risk map. The parameter data group 123 includes data stored in the storage unit 120 in advance, for example, before shipment of the surrounding environment recognition device 10.

The travel risk map data group 124 includes data on a travel risk map indicating a relationship between each position around the vehicle 2 and the travel risk of the vehicle 2, that is, the risk when the vehicle 2 travels at the position. It is an aggregate.

The communication unit 130 transmits and receives data to and from other devices mounted on the vehicle 2 based on various protocols. The communication unit 130 includes, for example, a network card that conforms to a communication standard such as Ethernet (registered trademark) or CAN (Controller Area Network).

The in-vehicle display control device 20 is connected to the display device 90, and includes a processing unit 200, a storage unit 220, a communication unit 230, and a screen input / output unit 240. The in-vehicle display control device 20 sends a notification to the driver regarding driving support of the vehicle 2 through the display device 90 based on information output from the surrounding environment recognition device 10 and information output from the travel control device 70. It is configured to perform by voice and screen.

The processing unit 200 includes a memory such as a CPU and a RAM, for example. The processing unit 200 includes a travel risk level map acquisition unit 201, a control plan information acquisition unit 202, and a travel risk level map display control unit 203 as parts for realizing the functions of the in-vehicle display control device 20. The processing unit 200 performs a process corresponding to each unit by executing a predetermined operation program stored in the storage unit 220.

The driving risk map acquisition unit 201 acquires data of the driving risk map output from the surrounding environment recognition device 10 and stores the data in the storage unit 220.

The control plan information acquisition unit 202 acquires the control plan information of the vehicle 2 output from the travel control device 70 and stores it in the storage unit 220.

The travel risk map display control unit 203 displays the travel risk map on the screen of the display device 90 via the screen input / output unit 240 based on the travel risk map data stored in the storage unit 220.

The storage unit 220 includes, for example, a storage device such as an HDD, a flash memory, and a ROM, and a memory such as a RAM. The storage unit 220 stores a program executed by the processing unit 200, a data group necessary for realizing the system, and the like.

The communication unit 230 transmits and receives data to and from other devices mounted on the vehicle 2 based on various protocols. The communication unit 230 includes, for example, a network card that conforms to a communication standard such as Ethernet or CAN.

The screen input / output unit 240 outputs screen display information to the display device 90 and acquires touch panel operation information performed on the screen of the display device 90 by the user.

The own vehicle position determination device 30 is a device that measures the geographical position of the vehicle 2 and provides the information. The own vehicle position determination device 30 is configured by, for example, a global navigation satellite system (GNSS) reception device. In that case, the own vehicle position determination device 30 may be configured to simply provide a positioning result based on the radio wave received from the GNSS satellite. Alternatively, by using information that can be acquired from the external sensor group 40 and the vehicle sensor group 50 such as the moving speed and traveling azimuth of the vehicle 2, interpolation and error correction are performed on the positioning result by the radio wave received from the GNSS satellite. The vehicle position determining device 30 may be configured as described above.

The external sensor group 40 is a sensor group that can recognize obstacles (other vehicles, bicycles, pedestrians, fallen objects, etc.) and characteristic objects (road signs, white lines, landmarks, etc.) around the vehicle 2. is there. The outside world sensor group 40 includes, for example, a camera device, a radar, a laser radar, a sonar, and the like. The external sensor group 40 is connected to the detected information about obstacles and features around the vehicle 2 (for example, relative distance and relative angle from the vehicle 2) and the external sensor group 40 and the surrounding environment recognition device 10. Output on an in-vehicle network such as CAN. The surrounding environment recognition device 10 is configured to obtain an output result from the external sensor group 40 through the in-vehicle network. In this embodiment, the external sensor group 40 is configured to perform processing for detecting an obstacle or a feature. However, the surrounding environment recognition device uses signals and data output from the external sensor group 40. 10 and other devices may perform these detection processes.

The vehicle sensor group 50 is a device group that detects the state of various parts related to the movement of the vehicle 2 (for example, travel speed, steering angle, accelerator operation amount, brake operation amount, etc.). For example, the vehicle sensor group 50 periodically outputs these detected state quantities on an in-vehicle network such as CAN. The surrounding environment recognition device 10 and other devices connected to the in-vehicle network are configured to be able to acquire the state quantities of various components output from the vehicle sensor group 50 through the in-vehicle network.

The map information management device 60 is a device that manages and provides digital map information around the vehicle 2. The map information management device 60 is constituted by, for example, a navigation device. The map information management device 60 includes, for example, digital road map data of a predetermined area including the periphery of the vehicle 2, and the vehicle on the map is based on the position information of the vehicle 2 determined by the own vehicle position determination device 30. 2, that is, a road or lane on which the vehicle 2 is traveling is specified. Moreover, it is comprised so that the present position of the specified vehicle 2 and its surrounding map data may be provided to the surrounding environment recognition apparatus 10 via vehicle-mounted networks, such as CAN.

The traveling control device 70 is an ECU for realizing an advanced driving assistance system (ADAS: Advanced Driver Assistance Systems) of the vehicle 2 for the purpose of improving the fuel consumption performance, safety, convenience, and the like of the vehicle 2. Based on the information output from the surrounding environment recognition device 10, the travel control device 70, for example, issues an instruction to the actuator group 80 to automatically control acceleration / deceleration and steering of the vehicle 2, or the in-vehicle display control device 20. Information provision and warning are output to the driver via the display device 90.

Actuator group 80 is a device group that controls control elements such as steering, brakes, and accelerators that determine the movement of vehicle 2. The actuator group 80 is configured to control the movement of the vehicle 2 based on operation information such as a steering wheel, a brake pedal, and an accelerator pedal by the driver and a target control value output from the travel control device 70.

FIG. 2 is a diagram showing an example of a travel risk map represented by the travel risk map data group 124 of the present embodiment.

The travel risk map data group 124 is data representing a travel risk map indicating the travel risk of the vehicle 2 at each position around the vehicle 2. As shown in FIG. 2, the travel risk map data group 124 includes, for example, a predetermined region (−X _B m to X _{F in the} x direction) defined by an xy coordinate system centered on the current position of the vehicle 2. The traveling risk R (x, y) of the vehicle 2 for each position of the coordinate values (x, y) where x and y are variables are represented in -Y _R m to Y _L m) in the m and y directions. It is shown. Here, the x-axis 250 is a central axis that penetrates the vehicle 2 in the front-rear direction, and the positive direction of the x-axis 250 corresponds to the front direction of the vehicle 2. The y-axis 251 is a central axis that penetrates the front portion of the vehicle 2 in the left-right direction, and the positive direction of the y-axis 251 corresponds to the left direction of the vehicle 2. The values that can be taken by the coordinate values (x, y) may be continuous values (for example, function expression) or discrete values (for example, grid expression). In the example of the travel risk map shown in FIG. 2, coordinate values (x, y) are converted into discrete values (x = x ₋₅ , x ₋₄ ,..., X ₃₀ , y = y ₋₈ , y ₋₇ , .., Y ₈ ), the value of the travel risk R (x, y) is expressed on the grid map.

In the following description, the cell length (distance in the x-axis direction between points corresponding to each cell) and cell width (distance in the y-axis direction between points corresponding to each cell) of the travel risk map expressed by the grid map ) _Are represented by d _x and dy, respectively. That is, the cell length d _x and cell width d _y of each cell represent respectively the spacing in the longitudinal direction and the transverse direction of the vehicle 2 for each position running risk is shown in the traveling risk map. In the example of FIG. 2, d _x and _dy are common to all cells in the travel risk map, but different d _x and _dy may be used depending on the position of the cell.

In the following, a few number of forward cell N _x of the cells present in the positive x-axis direction of the running the risk map (except x ₀₎ _+, number rear cell the number of cells present in the negative x N _x-, y the number of cells present in the axial positive direction (except for y ₀₎ number to the left cell N _{y +,} the number of right cell number of cells present in the y-axis negative direction N _y-, in which a represents respectively. When d _x and _dy are common, the front length X _F , the rear length X _B , the left length Y _L , and the right length representing the length in each direction of the travel risk map shown in FIG. Between Y _R and the cell length d _x , cell width _dy, and the number N _{x +} , N _x− , N _{y +} , N _y− of each of the front, rear, left and right cells, the following formulas (1) to (4) A relationship is established.
X _F = N _{x +} · d _x (1)
X _B = N _x− · d _x (2)
Y _L = N _{y +} · d _y (3)
Y _R = N _y− · d _y (4)

In FIG. 2, for example, the value of the travel risk R (x ₁₇ , y ₋₄ ) stored in the cell of the coordinate value (x ₁₇ , y ₋₄ ) is relative to the vehicle 2 corresponding to this coordinate value. This corresponds to the travel risk of the vehicle 2 at the position. Here, the value of the travel risk R (x, y) stored in each cell of FIG. 2 is normalized by integrating the risk due to the interaction between the vehicle 2 and the environmental elements around the vehicle 2 in the cell. The higher the value, the higher the degree of danger when the vehicle 2 travels. In the example of FIG. 2, the value of the travel risk R (x, y) of the vehicle 2 in each cell is represented by hatching, and the darker the hatching, the higher the travel risk.

Subsequently, the operation of the traveling control system 1 will be described with reference to FIGS. The surrounding environment recognition device 10 of the travel control system 1 according to the present embodiment includes a vehicle 2 and a vehicle acquired from the own vehicle position determination device 30, the external sensor group 40, the vehicle sensor group 50, and the map information management device 60, which are external devices. 2. Based on the information about the surrounding environmental elements, the surrounding environment recognition process as described below is executed to create the travel risk map around the vehicle 2 as described above. Then, the generated travel risk degree map is output to the in-vehicle display control device 20 and the travel control device 70. For example, the travel control device 70 plans a trajectory that allows the vehicle 2 to travel safely based on the acquired travel risk degree map, and controls the travel of the vehicle 2 via the actuator group 80. The in-vehicle display control device 20 displays, for example, the acquired travel risk map and the control plan information output from the travel control device 70, and presents the state of the travel control system 1 to the driver and the occupant. By these operations, driving assistance of the vehicle 2 is performed.

FIG. 3 is a diagram showing a surrounding environment recognition processing flow 500 executed by the surrounding environment recognition device 10 in the travel control system 1 of the present embodiment.

First, the vehicle information acquisition unit 101 waits for a predetermined time in step S501. Here, the process waits for a period of time until the driving risk map generation is triggered for the surrounding environment recognition device 10 without proceeding with the processing. The trigger may be applied by a timer so that the travel risk map is generated at regular intervals, or may be applied on demand by detecting the necessity of updating the travel risk map.

Next, in step S502, the vehicle information acquisition unit 101 acquires information about the vehicle 2 from the vehicle information data group 121 of the storage unit 120 as the vehicle information necessary for the surrounding environment recognition process. Here, the position information of the vehicle 2 acquired from the own vehicle position determination device 30, the information related to the state of the vehicle 2 acquired from the vehicle sensor group 50, the control plan information of the vehicle 2 acquired from the travel control device 70, Etc. are acquired as own vehicle information. The information on the state of the vehicle 2 may indicate the current state of the vehicle 2 such as the speed, acceleration, steering angle, accelerator opening degree, yaw rate, etc. of the vehicle 2 or an average of past predetermined times (for example, 1 second). Statistical information related to the vehicle 2 may be shown like the speed, or predicted information related to the vehicle 2 like the predicted average speed for a predetermined time (for example, 5 seconds) in the future. As described above, these pieces of information are acquired from the own vehicle position determination device 30, the vehicle sensor group 50, the travel control device 70, and the like by the own vehicle information acquisition unit 101 at an appropriate timing via the vehicle network or the like. Information or information processed based on the information (for example, statistical information) is stored in the storage unit 120 as the vehicle information data group 121.

Next, in step S <b> 503, the surrounding environment element acquisition unit 102 acquires information about the environment elements around the vehicle 2 from the surrounding environment element information data group 122 of the storage unit 120 as the surrounding environment element information necessary for the surrounding environment recognition processing. To do. Here, digital road map data related to roads around the vehicle 2 acquired from the map information management device 60 and recognition data of various environmental elements around the vehicle 2 acquired from the external sensor group 40 are acquired as peripheral environment element information. To do. The recognition data of environmental elements around the vehicle 2 includes obstacles (other vehicles, people, fallen objects, etc.), road shapes (road edges, white lines, stop lines, zebra zones, etc.), road surface conditions (freezing, puddles, pots) Information indicating the recognition status such as hall). As described above, these pieces of information are acquired from the external sensor group 40 and the map information management device 60 by the peripheral environment element acquisition unit 102 through the vehicle network or the like at an appropriate timing, and are stored in the storage unit 120 in the peripheral environment element. The information data group 122 is stored. This may be appropriately integrated by so-called fusion processing.

Subsequently, in step S504, the environmental element movement prediction unit 103 determines whether or not environmental elements (vehicles, people, etc.) that can move around the vehicle 2 are within a predetermined time based on the surrounding environmental element information acquired in step S503. The movement prediction information indicating how to move is generated. Here, recognition information (relative position, moving direction, moving speed, etc.) represented by the surrounding environment element information related to the environment element, and surrounding conditions (road shape, traffic rules, obstacles) represented by the surrounding environment element information related to the environment element Etc.), the movement for each environmental element is predicted. The movement prediction information is expressed, for example, by a list of predetermined time (for example, 1 second, 2 seconds,...) And estimated position information at the time.

Next, in step S505, the travel risk level map creation unit 106 executes a travel risk level map parameter determination process based on the information related to the state of the vehicle 2 acquired as the vehicle information in step S502. This driving risk map parameter determination process is a process for determining parameters related to the driving risk map created in the following steps and storing them in the storage unit 120 as part of the parameter data group 123. Details of the travel risk map parameter determination processing will be described below with reference to FIGS. 4 and 5.

Subsequently, in step S506, the existence time range determination unit 104 determines the vehicle based on the vehicle information acquired in step S502 and the parameters related to the travel risk map determined in the travel risk map parameter determination process in step S505. The vehicle presence time range determination process 600 for determining the second existence time range map is executed. Details of the vehicle existence time range determination processing 600 will be described below with reference to FIGS. 6 and 7.

Next, in step S507, the existence time range determination unit 104 determines an environment element existence time range determination process 700 that determines an existence time range map of each environment element based on the result of the surrounding environment element movement prediction performed in step S504. Execute. Details of the environment element existence time range determination processing 700 will be described below with reference to FIG.

Subsequently, the travel risk map creating unit 106 executes a travel risk map creating process 800 for creating a travel risk map around the vehicle 2 in step S508. Here, based on the vehicle 2 existing time range map determined in step S506, the environmental element existing time range map determined in step S507, and the surrounding environment element information acquired in step S503, the vehicle 2 travels around the vehicle 2 Create a risk map. Details of the travel risk map creation processing 800 will be described below with reference to FIGS. 9 and 10.

When the travel risk map creation processing 800 in step S508 is completed, the travel risk map providing unit 107 transmits the created travel risk map data to the in-vehicle display control device 20, the travel control device 70, and the like in step S509. Output. The data format of the output travel risk map will be described below with reference to FIG.

After executing the above-described steps S501 to S509, the process returns to step S501, and these steps are repeatedly executed.

<Driving risk map parameter determination process (S505)>
Next, the driving risk map parameter determination process executed in step S505 of FIG. 3 will be described. In the travel risk map parameter determination process, the expression format of the travel risk map is determined according to the policy described below, and the parameters corresponding to the expression format are determined.

The travel risk map is used, for example, when the travel control device 70 plans the travel path of the vehicle 2. If the target time of the planned travel path is T seconds, the travel risk map needs to represent at least a region where the vehicle 2 travels in T seconds. When the travel speed of the vehicle 2 is v, in the traveling direction of the vehicle 2 (x-axis direction), the distance L _x that the vehicle 2 travels in T seconds is expressed by the formula L _x = T · v, and the travel risk level The area to be expressed on the map extends in proportion to the traveling speed v. On the other hand, in the lateral direction (y-axis direction), the distance L _y traveled by the vehicle 2 in T seconds is expressed by the equation L _y = r · (1−cos (v · T / r)) where r is the turning radius. Expressed. Here, when the lateral acceleration is large, the riding comfort is deteriorated. _Therefore , when the maximum allowable lateral acceleration is A _lat , the minimum turning radius at the speed v is determined as r = v ² / A _lat . By substituting this into the above equation, the following equation (5) is obtained.
L _y = (v ² / A _lat ) · (1-cos (A _lat · T / v)) (5)

Here, when v = A _lat T / w, the equation (5) can be transformed into the following equation (6).
L _y = A _lat T ² (1-cosw) / w ² (6)

In the formula (6), brought close to w in 0, _{L y} approaches _A

lat

^T 2/2. This distance _{L y} of lateral vehicle 2 progresses, irrespective of the running speed v, which means that within a certain value _A lat ^T 2/2.

On the other hand, the accuracy of the travel risk map required in the travel track planning changes according to the travel speed of the vehicle 2. For example, when it is necessary to control the vehicle 2 that sews a gap at a low speed, such as a parking lot or an alley, an expression with a fine granularity (for example, 10 cm) is required in the travel risk map. On the other hand, when the vehicle 2 is traveling at a high speed like an expressway, in consideration of the accuracy with which the vehicle 2 can be controlled, the travel risk map is displayed with a fine granularity (for example, 10 cm) with respect to the traveling direction of the vehicle 2. There is no need to express. In general, the danger level relating to vehicle travel is determined on a time scale, such as TTC (Time To Collation) used as an index of the collision risk degree. From these facts, it is considered that it is a time scale that requires a certain accuracy in the expression of the travel risk map.

Therefore, in view of the above, in the present embodiment, in the travel risk map expressed by a grid map as shown in FIG. 2, the length d _x of each cell in the traveling direction of the vehicle 2, that is, the front-rear direction is set as the vehicle 2. Is changed according to the traveling speed v. Specifically, the length d _x of each cell is changed in proportion to the traveling speed v so as to satisfy the relationship d _x = a · v (a is a positive constant). Here, a is a value corresponding to the expression accuracy of the travel risk map on the time scale. On the other hand, the width d _y of each cell in the transverse direction of the vehicle 2 is set to a constant value relative to the running speed v of the vehicle 2. At this time, the vehicle 2 such that the area to proceed to T seconds is at least expressed on running the risk map, the length and d _x and width d _y of each cell, the number of cells is set. For example, the number of cells N _{x + in} the traveling direction of the vehicle 2, that is, the positive x-axis direction, and the number of cells N _{y +} and N _{y− in} the lateral direction of the vehicle 2, that is, the y-axis positive and negative directions, 8).
N _{x +} = L _x / d _x = T / a (7)
N _{y ±} = L _y / d _y = A _lat T ² / 2d _y (8)

In the equations (7) and (8), the number of cells N _{x +} , N _{y +} and N _y− are all expressed as constants that do not depend on the traveling speed v. Therefore, the number of cells required for the travel risk map can always be kept constant regardless of the travel speed v of the vehicle 2. This means that the memory usage necessary for the travel risk map can be defined to a constant value, and it is easy to design with a built-in device with memory restrictions such as the surrounding environment recognition device 10. can do.

Further, as described above, by setting the length d _x of each cell in the traveling direction of the vehicle 2 in proportion to the traveling speed v of the vehicle 2, it can be expressed as d _x = a · v. Therefore, the time T _xcell in which the vehicle 2 travels forward a distance corresponding to one cell is calculated as T _xcell = d _x / v = a, and is constant regardless of the travel speed v. This means that, for example, if a = 0.1 is set, the expression accuracy in units of 0.1 seconds can be maintained in the travel risk map expressed in a time scale.

On the other hand, the lateral direction and the distance L _y of the vehicle 2 travels within the predetermined time as described above is constant regardless of the traveling speed v, so as to satisfy the required accuracy in a fixed width d _y of each cell You only have to set it. For example, when it is desired to maintain the expression accuracy in units of 0.1 seconds, the distance that the vehicle 2 travels in the horizontal direction in 0.1 seconds can be calculated from the above equation (6) by L _y = A _lat · (0.1) ² / 2 = A _lat / 200. Therefore, if d _y = A _lat / 200, the required accuracy in the horizontal direction can be maintained.

However, if the value of the cell width d _y determined as described above is very small compared to the recognition accuracy of the external sensor group 40, travel risk map in the lateral direction it will be expressed finely than necessary, This leads to unnecessary consumption of memory. Therefore, such a case may be set cell width d _y in accordance with the recognition accuracy of the external sensor group 40.

Also, without the common cell width d _y throughout running the risk map may be increased as the distance from the x-axis 250. Specifically, for example, the horizontal position y _n of each cell (where n is an integer, n is an integer from −8 to 8 in the example of FIG. 2)), y _n = A _lat · (a · n ) is set to ^2/2. As described above, a is a value corresponding to the expression accuracy of the travel risk map on the time scale, for example, a = 0.1 seconds. In this case, the cell width d _y of each cell varies depending on the lateral position y _n, similarly to the cell length d _x a time on the scale, it can always be maintained the representation accuracy of a seconds. In this way, the number of cells N _{y +} and N _y− in the horizontal direction can be kept small compared to the case where the cell width _dy is fixed, and thus the memory consumption can be further reduced.

In the present embodiment, in the travel risk map parameter determination process, the length d _x of each cell of the travel risk map is determined based on the travel speed v of the vehicle 2 according to the policy described above, and each cell You can determine the width d _y. And the parameter according to these determined values can be determined.

Incidentally, when changing in proportion to the length d _x of each cell as described above to the running speed v of the vehicle 2, for example, as shown in the graph of FIG. 4, so as not to change the d _x is less than the predetermined speed It is preferable to make it. FIG. 4 is an example of a graph showing the relationship between the traveling speed v of the vehicle 2 and the cell length d _x of the traveling risk map. In the graph 401 of FIG. 4, the horizontal axis represents the traveling speed v of the vehicle 2, the vertical axis represents the cell length d _x of the driving risk map. In the present embodiment, as indicated by a broken line 411 in the graph 401, when the traveling speed v is equal to or greater than a predetermined value _Vth , the cell length d _x is changed in proportion to the traveling speed v while the traveling speed v is predetermined. when less than the value _{V th,} the cell length _{d x} a fixed value _{d x0.} In this way, it is possible to avoid making the cell length d _x smaller than necessary when the vehicle 2 is traveling at a low speed. That is, if the cell length d _x is simply proportional to the speed, the cell length d _x is required for the accuracy required for the recognition accuracy of the external sensor group 40 and the safety judgment when the traveling speed v is small. As a result, the memory is unnecessarily consumed. Therefore, when the travel speed v as described above is smaller than the predetermined value V _th, by the cell length d _x a fixed value d _x0, you can avoid unnecessary memory consumption.

In the above description, for the sake of simplicity, it is assumed that the vehicle 2 is traveling at a constant traveling speed v, and the distance L _x traveled by the vehicle 2 in T seconds is described as L _x = T · v. The vehicle 2 may accelerate while traveling. In this case, if the maximum longitudinal acceleration of the vehicle 2 is A _lon , the distance L _x that the vehicle 2 travels in T seconds is expressed by the following equation (9).
_{_{L x = T · v + A}} lon · T 2/2 ··· (9)

The broken line in the graph 401 412 _is a straight line indicating the _{d x = (T · v +} A lon · T 2/2) / N x + relationship. When the distance L _x is expressed by Expression (9), V _th is set so that the bent portion of the broken line 411 is positioned on the broken line 412 as shown in the graph 401. _{_{_{That, d x0 = (T · V}}} th + A lon · T 2/2) / N x + a to satisfy the relation, the threshold _{V th} of the driving speed v which changes in proportion to the cell length _{d x} to the running speed v It is possible to cope with the case where the vehicle 2 accelerates while traveling.

Further, the position of the vehicle 2 in the travel risk map may be changed according to the travel speed v of the vehicle 2. For example, when the traveling speed v is high, the vehicle 2 does not travel backward. Therefore, in this case, there is no need to express the travel risk for the rear of the vehicle 2, and the rear length X _B of the travel risk map shown in FIG. 2 may be set to X _B = 0. On the contrary, when the traveling speed v is low, that is, when the vehicle 2 travels at a low speed or stops, the vehicle 2 may travel backward due to the back travel. Therefore, in this case, it is important to express the degree of travel risk with respect to the rear of the vehicle 2, and it is necessary to satisfy X _B > 0. On the other hand, when the cell length d _x is a fixed value d _x0 when v <V _th as described above, the front length X _F of the travel risk map is larger than the distance L _x when the travel speed v is low. Thus, the traveling risk level in front of the vehicle 2 is excessively expressed.

Therefore, in the present embodiment, in order to avoid excessively expressing the driving risk in front of the vehicle 2 as described above, the position of the vehicle 2 on the driving risk map is determined in the driving risk map parameter determination process. The parameter is determined so as to change according to the traveling speed v. More specifically, for example, as shown in the graph of FIG. 5, the travel risk map of the anterior length X _F and the rear length X _B a may be set respectively according to the running speed v. FIG. 5 is an example of a graph showing the relationship between the travel speed v of the vehicle 2 and the lengths X _F and X _B in the front-rear direction of the travel risk map and the number of cells N _{x +} and N _x− . In the graph 402 of FIG. 5, the horizontal axis represents the traveling speed v of the vehicle 2, the upper direction of the vertical axis represents the forward length X _F of the traveling risk map, under the direction of the longitudinal axis of the rear length X _B Represents. Thick line 421 of the graph 402 represents the relationship between the traveling speed v and the front length X _F in the present embodiment, the thick line 422 represents the relationship between the traveling speed v and the rear length X _B according to this embodiment. In the graph 403 of FIG. 5, the horizontal axis represents the traveling speed v of the vehicle 2, and the vertical axis represents the number of cells in the traveling risk map in the front-rear direction of the vehicle 2. Dashed 431 of graph 403 represents the traveling speed v and the front cell number N _{x +} relationship in the present embodiment, the dashed line 432 represents the traveling velocity v and the rear cell number N _x- relationship in this embodiment.

The distance L _x− that the vehicle 2 travels backward while accelerating in T seconds is obtained by using the above-described equation (9), where A _lon− (where A _lon− <0) is the maximum longitudinal acceleration when the vehicle 2 travels backward. _{_{Te, L x- = | T · v}} + a lon- · T 2/2 | can be expressed as. Therefore, in the present embodiment, for example, as indicated by

thick lines

421 and 422 in the graph 402, when v <V _th , the number of forward cells N _{x +} and the following expressions (10) and (11) are satisfied respectively _: The number of backward cells N _x− is determined. Incidentally, a downward vertical axis in the graph 402 (negative direction) from the fact that the rear length X _B, shows the one obtained by reversing the sign of the right side of equation (11) by a thick line 422. Here, the relationship between the number of front cells N _{x +} and the front length X _{F and} the relationship between the number of rear cells N _x− and the rear length X _B are as shown in the above-described equations (1) and (2), respectively. is there. In Formula (10), X _F0 is the value of the forward length X _F when v = V _th .
_{_{^{X F = T · v + A}}} lon · T 2/2 ··· (10)
X _B = − (X _F −X _F0 ) (11)

In the manner described above, while meeting the requirements range for running the risk map (forward distance L _x, rear distance L _x-), as shown in the graph 403, the total number of cells in the longitudinal direction of the vehicle 2 (N _{x +} + N _x− +1) can be kept at a constant value N _x0 . Therefore, unnecessary memory consumption can be suppressed.

Note that the longitudinal direction of the running risk map as described above, because respectively control the length X _F and X _B while keeping the total number of cells in the constant position with respect to the traveling direction of the vehicle 2 in the traveling risk map This corresponds to changing (the number of rear cells N _x− ) according to the traveling speed v. That is, in the example of the graph 402 in FIG. 5, as shown by the graph 403, the number of rear cells N _x− changes according to the traveling speed v.

In the method for determining the expression format of the travel risk map described above, the current travel speed of the vehicle 2 may be used as the travel speed v of the vehicle 2, or an average over a past predetermined time (for example, 1 second). Statistical speeds such as speed may be used. Moreover, the prediction information regarding the vehicle 2 may be shown like a predicted average speed for a predetermined time in the future (for example, 5 seconds).

In the travel risk map parameter determination process of the present embodiment, the cell position (cell length, cell width) of the travel risk map and the position of the vehicle 2 are set as described above, and parameters according to these setting results. Is stored in the storage unit 120 as the parameter data group 123. By creating a travel risk map using the parameters determined in this way, memory consumption is suppressed while satisfying the required accuracy and required range for the travel risk map necessary for judging the safety of the vehicle 2 for travel. Is possible.

<Own vehicle existing time range determination processing 600 (S506)>
Next, the own vehicle presence time range determination process 600 executed in step S506 of FIG. 3 will be described. FIG. 6 is a diagram illustrating an example of a flowchart of the own vehicle presence time range determination process 600.

First, the existence time range determination unit 104 acquires parameter data related to the travel risk map from the parameter data group 123 of the storage unit 120 in step S601. The parameter data relating to the travel risk map acquired here is the parameter data determined in the travel risk map parameter determination process in step S505 in FIG. 3 or the ROM or the like in advance before shipping the surrounding environment recognition device 10. The parameter data stored in the storage unit 120 is included.

Next, the existence time range determination unit 104 determines the driving distance D (x, y) at the position (x, y) corresponding to each cell of the travel risk map in step S602. Subsequently, in step S603, the existence time range determination unit 104 considers the vehicle speed, acceleration, jerk, and the like of the vehicle 2 based on the driving distance D (x, y) determined in step S602. The existence time range TED (x, y) of is calculated. Then, in step S604, the existence time range determination unit 104 constructs an existence time range map of the vehicle 2 based on the calculation result of the existence time range TED (x, y) performed in step S603. Set in the car information data group 121. If the process of step S604 is executed, the existing time range determining unit 104 ends the own vehicle existing time range determining process 600.

Details of the processing performed in steps S602 and S603 will be described with reference to FIG. FIG. 7 is a diagram showing an example of the existence time range map 300 of the vehicle 2 in the own vehicle information data group 121.

The driving distance D (x, y) determined in step S602 is a distance corresponding to the road until the vehicle 2 reaches the position of the coordinate value (x, y). The trajectory for the corresponding position is, for example, a fan-shaped arc having a center point on the y-axis 321 in FIG. 7 and passing through the origin and the corresponding position, or a spline curve whose tangent line between the origin and the corresponding position is the x-axis 320. Etc. are considered. In the existence time range map 300 illustrated in FIG. 7, a trajectory 331 with respect to (x _a , y _a ) and a trajectory 332 with respect to (x _b , y _b ) are shown. For example, the operating distance D (x, y) when the sector arc model is used is represented by the product of the sector radius r (x, y) and the sector central angle θ (x, y). The values of the radius r (x, y) and the central angle θ (x, y) with respect to the coordinate value (x, y) can be calculated using the following equations (12) and (13), respectively.
r (x, y) = (x ² + y ² ) / 2y (12)
θ (x, y) = arctan (x / (ry)) (13)

The existing time range TED (x, y) calculated in step S603 is a distribution expressing the probability that the vehicle 2 exists at the position at each time. In the presence time range map 300 of FIG. _{_{7, (x a, y a}} ) present time range TED _(x _{a, y} a) corresponding to _{a, (x _b,} _y b) present time corresponding to the range TED _{(x b} , Y _b ) are represented as

time probability distributions

301 and 302, respectively. In practice, since it is difficult to obtain a strict probability distribution, the

time probability distributions

301 and 302 may be approximated. For example, the average arrival time T _r (x, y) for the position may be treated as a representative value. Alternatively, approximation may be made with a Gaussian distribution in which the average value μ is T _r (x, y) and the variance value σ ² is f (T _r ). Here, the reason why the variance value σ ² is expressed by the function f of T _r is that the time zone in which the vehicle 2 can exist stochastically increases as time elapses. The average arrival time T _r (x, y) is calculated, for example, by dividing the driving distance D (x, y) by the traveling speed v using the traveling speed v of the vehicle 2 described above.

Here, in principle, the driving distance D (x, y) and the existence time range TED (x, y) need to be calculated for all cell positions in the travel risk map. When the cell size is fixed, the driving distance D (x, y) does not change even if the traveling speed v of the vehicle 2 changes. Therefore, by storing the calculation result in the storage unit 120 in advance. In step S602, the driving distance D (x, y) can be determined with reference to it. Therefore, it is possible to reduce the calculation amount. On the other hand, when the cell size is dynamically changed according to the traveling speed v of the vehicle 2 as in the present embodiment, the driving distance D (x, y) changes according to the traveling speed v. It is necessary to calculate the driving distance D (x, y) every time. In this case, it is necessary to calculate the existence time range TED (x, y) every time. As a result, there arises a problem that the amount of calculation increases compared to the case where the cell size is fixed.

Therefore, in this embodiment, as described above, when the cell length is dynamically changed according to the traveling speed v of the vehicle 2 by setting the cell length to be proportional to the traveling speed v. However, the increase in calculation amount is suppressed. This point will be described below.

When the existence time range at the traveling speed v (≧ V _th ) of the vehicle 2 is expressed as TED (x, y, v), this has the characteristics shown by the following formula (14).
TED (x, y, v)
= D (a · v, y) / v
= (V / V _th ) · D (a · V _th , y · V _th / v) / v
= TED (x, y · V _th / v, V _th ) (14)

The above formula (14) is derived from the above formulas (12) and (13) when the driving distance D (x, y) has the characteristics as the following formula (15).
D (k · x, k · y) = k · D (x, y) (15)

Expression (14) refers to the existence time range TED (x, y, V _th ) when the existence time range TED (x, y, v) at an arbitrary velocity v (≧ V _th ) is the velocity V _th . It means that it is obtained by. Therefore, in the present embodiment, the existing time range TED (x, y, V _th ) at the speed V _th is calculated in advance and stored in the storage unit 120 such as the ROM, so that steps S602 and S603 are performed. It is possible to greatly reduce the amount of calculation processing. When v < _Vth , the cell size is fixed as described above, so that the driving distance D (x, y) is calculated in advance as in the case where the conventional cell size is not changed. By storing the data in the storage unit 120 such as a ROM, the amount of calculation can be reduced.

As described above, in the present embodiment, the cell length d _x in the traveling direction of the vehicle 2 is set to be proportional to the traveling speed v, so that it is necessary to calculate the travel risk using the previous calculation result. It is possible to perform calculations and the amount of calculations is reduced. Unlike the present embodiment, when the cell size is changed without being proportional to the traveling speed v, it is difficult to perform the above-described pre-calculation, so the amount of calculation cannot be reduced. This point should be noted in the present invention.

<Environment Element Existing Time Range Determination Processing 700 (S507)>
Next, the environment element existence time range determination process 700 executed in step S507 of FIG. 3 will be described. FIG. 8 is a diagram illustrating an example of a flowchart of the environment element existence time range determination process 700.

First, the existence time range determination unit 104 refers to the surrounding environment element information data group 122 in step S701, and selects one of the environment elements existing around the vehicle 2.

Subsequently, in step S702, the existence time range determination unit 104 determines whether the environmental element selected in step S701 is a moving body such as another vehicle, a bicycle, or a pedestrian. As a result, if the environmental element is a moving object, the process proceeds to step S703, and if not, the process proceeds to step S706.

If it is determined in step S702 that the environmental element is a moving object, the existence time range determination unit 104 refers to the surrounding environmental element information data group 122 in step S703, and obtains a movement prediction result for the environmental element selected in step S701. Get the information shown.

Subsequently, in step S704, the existence time range determination unit 104 calculates the existence time range ETED (x, y) of the environment element at the position based on the movement prediction result of the environment element acquired in step S703. Note that the travel risk map is used to determine the risk of the trajectory of the vehicle 2, and therefore, it should not be assumed that the vehicle 2 draws a specific travel trajectory. Therefore, in the above-described own vehicle existence time range determination process 600, it is necessary to calculate the existence time range of the vehicle 2 for all cell positions. On the other hand, with respect to environmental elements, the travel trajectory is predicted to determine the degree of risk. Therefore, the existence time range may be calculated only for the cell position related to the predicted travel path of the environment element indicated by the movement prediction result acquired in step S703.

When the calculation of the existence time range of the environment element ends, the existence time range determination unit 104 sets the environment element existence time range map in the surrounding environment element information data group 122 based on the calculation result in step S705.

Subsequently, the existence time range determination unit 104 determines in step S706 whether all the environmental elements existing around the vehicle 2 have been selected in step S701. If there is an unselected environmental element, the process returns to step S701, and one of the environmental elements is selected in step S701, and then the process from step S702 onward is performed on the environmental element. On the other hand, when all the environmental elements have been selected, the existence time range determination unit 104 ends the environment element existence time range determination processing 700.

A vehicle presence time range map representing the vehicle 2 existence time range for each position around the current position of the vehicle 2 by the vehicle existence time range determination process 600 and the environment element existence time range determination process 700 described above, An environment element existence time range map representing the existence time range of each environment element for each position around the current position of 2 is determined.

<Driving risk map creation processing 800 (S508)>
Next, the travel risk map creating process 800 executed in step S508 of FIG. 3 will be described.

The travel risk map creation unit 106 calculates coordinate values (x, y) corresponding to each cell of the travel risk map according to the parameters determined by the travel risk map parameter determination process executed in step S505 of FIG. decide. Next, the travel risk determination unit 105 executes the vehicle 2 existence time range map created by the vehicle existence time range determination processing 600 executed in step S506 of FIG. 3 and the step S507 of FIG. The travel risk degree R (x, y) at the coordinate value (x, y) is calculated using the existing time range map of each environmental element created by the environment element existing time range determination processing 700. Subsequently, the travel risk level map creating unit 106 generates a travel risk level map based on the travel risk level R (x, y) calculated by the travel risk level determination unit 105, and travel risk level map data stored in the storage unit 120. Store in group 124.

The driving risk R (x, y) is, for example, a weighted integrated value of the risk caused by each environmental element, and is represented by, for example, the following expression (16). However, in Formula (16), r _i and w _i (i is an integer from 1 to n) represent a driving risk and a weighting coefficient for the environmental element i, respectively.
R (x, y) = w ₁ · r ₁ (x, y) +... + W _n · r _n (x, y) (16)

Or, the travel risk, R (x, y) may be calculated by the maximum value of the weighting of risk posed by the environmental factors (maximum value of _{_{w i · r i (x,}} y)).

Running the risk r _i on environmental element i, using the present time range map of the vehicle 2 that has been generated in step S506 in FIG. 3, the presence time range map of each environmental elements generated in step S507 in FIG. 3 Calculated. As an example, based on the degree of overlap between the probability distribution of the existence time range of the vehicle 2 in the own vehicle existence time range map and the probability distribution of the existence time range of each environmental element in the environment element existence time range map, The driving risk at each position on the map is calculated. A formula for calculating the travel risk R (x, y) of the vehicle 2 with respect to the environmental element i based on the probability distribution of the existence time range is expressed by, for example, the following formula (17). However, in the equation (17), p _{(x, y)} (t) represents a probability distribution of the existence time range of the vehicle 2, and p _{i (x, y)} (t) represents the existence time range of the environmental element i. Represents a probability distribution.

_{Alternatively} , using the representative value T _repre of the existing time range of the vehicle 2 and the representative value T ⁽ⁱ⁾ _repre of the existing time range of the environmental element i, for example, according to the following equation (18), the driving risk R (x, y ) May be calculated.

The above equation (18) is obtained by the function f (x) based on the absolute value of the difference between the representative value T _repre of the existing time range of the vehicle 2 and the representative value T ⁽ⁱ⁾ _repre of the existing time range of the environmental element i. It evaluates the driving risk. The function f (x) is a function that decreases in value as x increases. For example, the function f (x) can be expressed by an expression such as f (x) = a · exp (−bx ² ) using correction coefficients a and b. .

In Expression (18), the magnitude of the function f (x) and the degree of attenuation are determined using, for example, the correction coefficients a and b according to the representative value T _repre of the existing time range of the vehicle 2 and the vehicle speed of the vehicle 2. May be adjusted. Further, the probability distribution of the existence time range of the vehicle 2 and each environmental element may be approximated by a predetermined distribution (Gaussian distribution or the like) centered on the representative value, and the driving risk may be calculated by superimposing them.

According to the above calculation method, since the risk level is set by evaluating the degree of intersection of the vehicle 2 and each environmental element on the time axis at a predetermined position, the travel risk level of the vehicle 2 is highly accurate in a form that matches the actual situation. Can be calculated.

An example of the travel risk map generated by the travel risk map creation process 800 will be described with reference to FIGS.

FIG. 9 is a diagram illustrating an example of a traveling road environment of the vehicle 2. FIG. 9 shows a scene in which the vehicle 2 is traveling on an opposite two-lane road. In the scene of FIG. 9, another vehicle 452 is parked on the road in the opposite lane near the vehicle 2, and the other vehicle 451 is about to pass the parked vehicle (other vehicle 452). Since this road is not wide enough, the other vehicle 451 needs to protrude into the opposite lane (the lane in which the vehicle 2 is traveling) in the process of overtaking the parked vehicle. In addition, the other vehicle 453 is traveling at the same speed as the vehicle 2 in front of the vehicle 2. In FIG. 9,

areas

461, 462, and 463 indicated by hatching indicate the ranges of predicted traveling tracks of the

other vehicles

451, 452, and 453, respectively. On the other hand, 460 indicated by a dotted line indicates a predicted traveling path when the vehicle 2 continues traveling so far.

FIG. 10 is a generation example of a travel risk map in the scene shown in FIG. A travel risk map 801 on the left side of FIG. 10 shows an example of a travel risk map at _a speed v = V _a (> V _th ), and a travel risk map 802 on the right side of FIG. 10 shows a speed v = V _b (> An example of the travel risk map at V _a ) is shown. As described above, since the length of the cell in the traveling direction of the vehicle 2 increases in proportion to the traveling speed v of the vehicle 2, the travel risk map 802 is more forward of the vehicle 2 than the travel risk map 801. (X _Fb > X _Fa ).

In the

travel risk maps

801 and 802, different travel risk levels are set in areas 810 to 814, respectively.

Regions

810 and 811 correspond to a non-road region and a roadside belt region on the traveling lane side of the vehicle 2, and a region 812 corresponds to a traveling lane region. An area 813 corresponds to an oncoming lane area including a roadside zone, and an area 814 corresponds to a non-road area on the oncoming lane side. Although these regions 810 to 814 are not shown in the travel risk map 802, they are the same as the travel risk map 801. The travel risk in the areas 810 to 814 shown in the

travel risk maps

801 and 802 are recognized as road attributes indicated by static environmental elements, and the travel risk is assigned to the corresponding cell according to the respective travel risk models. It is obtained by integrating.

Further, an area 815 of the travel risk map 801 and an area 817 of the travel risk map 802, an area 816 of the travel risk map 801, and an area 818 of the travel risk map 802 are travel risk levels by the

other vehicles

451 and 452, respectively. Is expressed. Since the other vehicle 452 is a parked vehicle and continues to exist on the spot, a very high traveling risk is set in the vicinity of the other vehicle 452 regardless of the speed of the vehicle 2 as shown in

regions

816 and 818. In these areas, the collision probability is 1 when the vehicle 2 travels through the corresponding position. On the other hand, the other vehicle 451 is a moving vehicle, and the region where the vehicle 2 and the existence time range overlap varies depending on the relative speed with the vehicle 2. For example, if the running speed of the vehicle 2 is v = V _a, at the timing when the other vehicle 451 comes protrudes driving lane of the vehicle 2, the traveling trajectory and temporally interlaced in running track and another vehicle 451 of the vehicle 2 To do. Therefore, the travel risk is set as in the area 815 in the travel risk map 801. On the other hand, when v = _Vb where the traveling speed of the vehicle 2 is relatively high, the traveling track of the vehicle 2 and the traveling track of the other vehicle 451 are the timing before the other vehicle 451 protrudes into the traveling lane of the vehicle 2. Intersect with each other in time. Therefore, the travel risk is set as in the area 817 in the travel risk map 802.

Based on this, for example, when the travel control device 70 performs travel control of the vehicle 2 using the travel risk map 801, the travel control device 70 avoids the region 815 in order to avoid a collision risk with the other vehicle 451. A track that travels to the left of the travel lane 812 is selected. On the other hand, when the travel control of the vehicle 2 is performed using the travel risk map 802, a track that travels in the center of the travel lane is selected without selecting an unnecessary avoidance track. In this way, it is possible to easily determine a safe and comfortable traveling path according to the situation.

<Output data format of travel risk map>
Next, the data format of the travel risk map will be described. FIG. 11 is an explanatory diagram showing an example of the data format 850 of the travel risk map output by the travel risk map providing unit 107 of the surrounding environment recognition device 10 according to the present embodiment. However, illustration of header information related to the communication protocol is omitted.

As shown in the data format 850 of FIG. 11, the driving risk map data output from the surrounding environment recognition apparatus 10 includes a total cell number 851, a cell number 852 in the X direction, a cell number 853 in the Y direction, and a cell in the X direction. Length 854, cell length 855 in the Y direction, own vehicle position 856, own vehicle speed 857, travel risk information 858, and the like.

The total number of cells 851 is data indicating the total number of cells constituting the travel risk map, which is equivalent to the product of the number of cells 852 in the X direction and the number of cells 853 in the Y direction. The cell length 854 in the X direction and the cell length 855 in the Y direction are data indicating the length in the front-rear direction and the left-right direction of the vehicle 2 of each cell in the travel risk map, respectively. is _{d x,} it corresponds to the cell width _{d y.} The own vehicle position 856 is data indicating which cell position the vehicle 2 is set on the travel risk map, and is expressed by, for example, coordinates of (position in the X direction, position in the Y direction). This is information required when the position of the vehicle 2 on the travel risk map is changed according to the travel speed v as described with reference to FIG. The own vehicle speed 857 is data indicating the traveling speed v of the vehicle 2 as a reference when the travel risk map is generated. The traveling speed v of the vehicle 2 here may be a current speed, a statistical speed, or a speed based on a future prediction as described above. The travel risk information 858 is data indicating information related to the travel risk of each cell in the travel risk map. The driving risk is expressed by a numerical value (for example, 0 to 100) within a predetermined range. For example, the larger the numerical value, the higher the risk.

In this embodiment, since the cell length (d _x ) is proportional to the traveling speed v of the vehicle 2, the value of the cell length 854 in the X direction is the value of the own vehicle speed 857 in the data of the travel risk map. Changes in proportion to As described with reference to FIG. 5, since the position of the vehicle 2 on the travel risk map changes according to the travel speed v, the value of the position 856 (particularly the x component) of the host vehicle is also the value of the host vehicle speed 857. It changes according to the value. On the other hand, other data values of reference numerals 851 to 853 and 855 do not change even if the value of the host vehicle speed 857 changes. That is, since the value of the total number of cells 851 does not change, the output data length of the travel risk map is a fixed length. Therefore, in the travel control device 70 and the in-vehicle display control device 20 that receive and process the data of the travel risk map from the surrounding environment recognition device 10, the amount of memory used for the process related to the travel risk map is deterministically estimated. This has the advantage of being easy to design.

<Driving risk map display processing of in-vehicle display control device 20>
Next, the operation of the in-vehicle display control device 20 will be described with reference to FIGS. FIG. 12 is a diagram illustrating an example of a travel risk map display processing flow 900 executed by the in-vehicle display control device 20.

First, the travel risk level map acquisition unit 201 acquires the travel risk level map output from the surrounding environment recognition apparatus 10 according to the data format 850 of FIG. 11 in step S901.

Next, the control plan information acquisition unit 202 acquires the control plan information output from the travel control device 70 in step S902. The control plan information includes information on the travel path determined by the travel control device 70 based on the travel risk map.

In step S903, the travel risk map display control unit 203 generates screen information to be transmitted to the driver or the occupant using the travel risk map and the control plan information acquired in steps S901 and S902. . Then, the generated screen information is output to the display device 90 via the screen input / output unit 240 and displayed on the display device 90.

FIG. 13 is a diagram illustrating an example of a display screen in the display device 90.

Display screens

1001 and 1002 correspond to display screen examples when the

travel risk maps

801 and 802 in FIG. 10 are acquired, respectively. In the present embodiment,

panels

1011 and 1021 for displaying cognitive information by sensors and maps are arranged on the left side of the

display screens

1001 and 1002, respectively, and the travel risk map and the travel control device 70 are determined on the right side of the display screen.

Panels

1012, 1022 for displaying the travel trajectories are arranged. Note that the travel risk degree maps of the

panels

1012, 1022 are represented by

distance scales

1014, 1024 corresponding to the distance from the vehicle 2, respectively.

On the

display screens

1001 and 1002, as shown in the panel 1012 and the panel 1022, the traveling

tracks

1013 and 1023 of the vehicle 2 are superimposed on the traveling risk map. Accordingly, the driver or the occupant can grasp what kind of situation (risk) the vehicle 2 has traveled or how the vehicle 2 will travel in the future. In general, in the automatic driving control of a vehicle, a driver or an occupant may feel anxiety because he / she does not know what purpose the driving control system is controlling the vehicle. Therefore, like the

display screens

1001 and 1002 of the present embodiment, by showing the determination contents (traveling trajectory) of the traveling control system 1 and the grounds (traveling risk degree map and cognitive information), the driver and the occupant's anxiety. It becomes possible to reduce.

In addition, in this embodiment, since the length of the cell of the advancing direction changes in proportion to the traveling speed v of the vehicle 2 as described above, the display screen 90 in the display device 90 has a feature. Specifically, on the display screen 1002, the travel speed v is larger than that on the display screen 1001, and thus the display target range of the travel risk map extends to the front (traveling direction) of the vehicle 2. Further, although not shown in the example of FIG. 13, the position of the vehicle 2 on the travel risk map similarly changes according to the travel speed v. Specifically, when the position of the vehicle 2 changes as described with reference to FIG. 5, the position of the vehicle 2 approaches the center of the travel risk map as the travel speed v decreases and decreases, It looks like it gradually shifts upward. As described above, the change in the target area of the travel risk map on the display screen and the position of the vehicle 2 in accordance with the change in the travel speed of the vehicle 2 is one of the features of the present embodiment.

In the screen display method of FIG. 13 described above, as the speed v of the vehicle 2 increases, the display target range of the travel risk map increases in proportion to the increase. However, as the display target range of the travel risk map increases, the entire travel risk map is reduced (for example, in the front-rear direction) and displayed during high-speed travel due to restrictions on the screen size of the display device 90 or the like. , It may be necessary not to display a part. As a result, there is a possibility that the travel risk map becomes difficult to see during high speed travel. Therefore, a method of expressing the travel risk map on a time scale instead of a distance scale by using the fact that the travel risk map extends in proportion to the speed of the vehicle 2 can be considered.

FIG. 14 is a diagram illustrating an example of a display screen in the display device 90 when each is expressed by a distance scale and a time scale. In FIG. 14, a display screen 1003 is an example of a display screen on a distance scale when the traveling speed v of the vehicle 2 is smaller than the predetermined value _Vth , and the display screen 1004 shows that the traveling speed v of the vehicle 2 is predetermined. The example of the display screen in the time scale in case it is more than the value _Vth is shown. In these display screens, as in the

display screens

1001 and 1002 shown in FIG. 13,

panels

1031 and 1041 for displaying recognition information by sensors, maps, etc. are arranged on the left side, and a driving risk map and the right side are displayed.

Panels

1032 and 1042 for displaying the traveling tracks determined by the traveling control device 70 are arranged. Further, on the

panels

1032 and 1042, the traveling

tracks

1033 and 1043 of the vehicle 2 are superimposed and displayed on the traveling risk map.

In this expression method, when v <V _th , the cell length d _x of the travel risk map is the fixed value d _x0 as described above, so that it is not expressed on the time scale like the display screen 1003. A travel risk map expressed by a distance scale 1034 corresponding to the distance from the vehicle 2 is displayed. On the other hand, when v ≧ V _th , a travel risk map expressed by a time scale 1044 corresponding to the arrival time of the vehicle 2 is displayed as in the display screen 1004. Thus, the travel risk map is expressed by switching between the distance scale and the time scale according to the travel speed of the vehicle 2. When expressed on a time scale, the display target range of the travel risk map is always constant even during high-speed travel, so that stable display is possible.

As described above, according to the present embodiment, by setting the cell length (d _x ) of the travel risk map so as to be proportional to the travel speed v, the required accuracy and requirements required for the safety judgment are set. While satisfying the range, the required number of cells in the travel risk map can always be kept constant. As a result, the amount of memory consumed by the travel risk map can be reduced and can be regulated to a constant value, and the design with a built-in device with memory restrictions becomes easy.

In addition, according to the present embodiment, by setting the cell length (d _x ) in the traveling direction of the vehicle 2 to be proportional to the traveling speed v, the calculation necessary for calculating the traveling risk is calculated in advance. It is possible to reduce the amount of calculation.

According to the embodiment of the present invention described above, the following operational effects are obtained.

(1) The surrounding environment recognition device 10 is mounted on the vehicle 2 and recognizes the surrounding environment of the vehicle 2. The peripheral environment recognition apparatus 10 includes a host vehicle information acquisition unit 101 that acquires host vehicle information regarding movement of the vehicle 2 including the traveling speed of the vehicle 2, and a peripheral environment that acquires peripheral environment element information for environmental elements around the vehicle 2. An element acquisition unit 102 and a travel risk determination unit 105 that determines travel risk levels at a plurality of positions around the vehicle 2 based on the vehicle information and the surrounding environment element information are provided. The interval between a plurality of positions in the front-rear direction of the vehicle 2, that is, the length d _x of each cell in the travel risk map changes according to the travel speed v of the vehicle 2. Since it did in this way, the danger required for judgment of safety can be calculated | required, suppressing the amount of calculations and memory consumption amount at the time of both high-speed driving and low-speed driving.

(2) The interval between a plurality of positions in the front-rear direction of the vehicle 2, that is, the length d _x of each cell in the travel risk map is such that the travel speed v of the vehicle 2 when the travel speed v of the vehicle 2 is equal to or greater than a predetermined value _Vth. It is assumed that it is constant when the traveling speed v of the vehicle 2 is less than a predetermined value _Vth . Since it did in this way, when the vehicle 2 is drive | working at low speed, it can avoid that the space | interval of the several position in the front-back direction of the vehicle 2 becomes small more than needed, and memory is not consumed unnecessarily.

(3) When the traveling speed v of the vehicle 2 is less than the predetermined value _Vth , the number of a plurality of positions behind the vehicle 2, that is, the rear length X _B of the traveling risk map, as the traveling speed v of the vehicle 2 decreases. It was decided to increase. Since it did in this way, when there exists a possibility that the vehicle 2 may drive | work back by back driving | running | working, a driving | running | working risk can be expanded in a required range.

(4) The number of the plurality of positions, that is, the total number of cells in the travel risk map is constant with respect to the change in the travel speed v of the vehicle 2. Since it did in this way, in the apparatus which receives and processes the data of the driving risk map from the surrounding environment recognition device 10, the amount of memory used for the processing related to the driving risk map can be estimated deterministically. Can be simplified.

(5) spacing of the plurality of positions in the transverse direction of the vehicle 2, that is, the width d _y of each cell of the traveling risk map was set to be constant with changes in the traveling speed v of the vehicle 2. Since it did in this way, the amount of calculation and memory consumption can be suppressed, maintaining the required precision of the risk degree with respect to a horizontal direction.

(6) spacing a plurality of positions in the transverse direction of the vehicle 2, that is, the width d _y of each cell of the traveling risk map as to become larger as the distance from the x-axis 250 is a central axis passing through the vehicle 2 in the longitudinal direction Also good. In this way, the memory consumption can be further reduced.

(7) The surrounding environment recognition device 10 further includes a travel risk map creating unit 106 that creates a travel risk map that represents the relationship between each of a plurality of positions around the vehicle 2 and the travel risk. Since it did in this way, the crossing relationship on the time axis of the vehicle 2 and each environmental element was projected on the parameter | index of driving | running | working risk, and the evaluation result with respect to the driving | running | working risk of the vehicle 2 was shown clearly in two-dimensional space. A travel risk map can be provided.

(8) The surrounding environment recognition device 10 determines the own vehicle existing time range indicating the existing time range of the vehicle 2 for each of a plurality of positions around the vehicle 2 based on the own vehicle information, and the surrounding environment element information Is further provided with an existence time range determination unit 104 that determines an environment element existence time range that represents the existence time range of the environment element for each of a plurality of positions around the vehicle 2. The travel risk level determination unit 105 determines travel risk levels at a plurality of positions based on the own vehicle presence time range and the environmental element presence time range determined by the presence time range determination unit 104. Since it did in this way, the driving | running | working risk degree of the vehicle 2 can be evaluated with high precision in consideration of the temporal change of the surrounding environment of the vehicle 2 and an environmental element.

(9) The in-vehicle display control device 20 displays information related to the vehicle 2 on the display device 90 mounted on the vehicle 2. The in-vehicle display control device 20 has been acquired by a travel risk map acquisition unit 201 that acquires a travel risk map representing travel risk levels at a plurality of positions around the vehicle 2, and the travel risk map acquisition unit 201. A travel risk map display control unit 203 that causes the display device 90 to display a travel risk map. The display target range of the travel risk map around the vehicle 2 changes according to the travel speed v of the vehicle 2. Since it did in this way, the danger required for judgment of safety can be expressed with a driving | running | working risk degree map, suppressing the amount of calculations and memory consumption about both the time of high speed driving | running | working and low speed driving | running | working.

(10) The travel risk map is divided into a plurality of cells respectively corresponding to a plurality of positions, and the cell size in the travel risk map is such that the travel speed v of the vehicle 2 is equal to or greater than a predetermined value _Vth. It changes according to the traveling speed v of the vehicle 2, and is constant when the traveling speed v of the vehicle 2 is less than a predetermined value _Vth . Since it did in this way, when the vehicle 2 is drive | working at low speed, it can avoid that the cell of a driving | running | working risk map becomes small more than necessary and memory is not consumed unnecessarily.

(11) When the travel speed v of the vehicle 2 is less than the predetermined value _Vth , the position of the vehicle 2 in the travel risk map changes according to the travel speed v of the vehicle 2. Specifically, the position of the vehicle 2 approaches the center of the travel risk map as the travel speed v of the vehicle 2 decreases. As described above, when there is a possibility that the vehicle 2 travels backward due to the back travel, the travel risk map is expanded to a necessary range while suppressing an increase in calculation amount and memory consumption. can do.

(12) The travel risk map is divided into a plurality of cells respectively corresponding to a plurality of positions. When the travel speed v of the vehicle 2 is equal to or higher than a predetermined value _Vth , the travel risk map is a time scale corresponding to the arrival time of the vehicle 2. It may be expressed as a distance scale corresponding to the distance from the vehicle 2 when the traveling speed v of the vehicle 2 is less than the predetermined value _Vth . In this way, it is possible to display a stable and easy-to-see travel risk map with the display target range of the travel risk map always being constant even during high-speed travel.

Note that the embodiment described above is an example, and the present invention is not limited to this. That is, various applications are possible, and all the embodiments are included in the scope of the present invention.

For example, in the above-described embodiment, each process of the surrounding environment recognition apparatus 10 is realized by executing a predetermined operation program using a processor and a RAM, but is realized by original hardware as necessary. It is also possible. Moreover, in said embodiment, the surrounding environment recognition apparatus 10, the vehicle-mounted display control apparatus 20, the own vehicle position determination apparatus 30, the external field sensor group 40, the vehicle sensor group 50, the map information management apparatus 60, the travel control apparatus 70, an actuator Although the group 80 and the display device 90 are described as separate devices, any two or more devices may be combined as necessary.

When each of the above processes is realized by the processor executing a predetermined operation program, information such as an operation program, a table, and a file for realizing each process includes a nonvolatile semiconductor memory, a hard disk drive, an SSD (Solid State). Or a non-transitory data storage medium that can be read by a computer such as an IC card, an SD card, or a DVD.

In the drawings, control lines and information lines considered necessary for describing the embodiment are shown, and all control lines and information lines included in an actual product to which the present invention is applied are not necessarily shown. Not necessarily. Actually, it may be considered that almost all the components are connected to each other.

The embodiments and various modifications described above are merely examples, and the present invention is not limited to these contents as long as the features of the invention are not impaired. Moreover, although various embodiment was described above, this invention is not limited to these content. Other embodiments conceivable within the scope of the technical idea of the present invention are also included in the scope of the present invention.

The disclosure of the following priority application is hereby incorporated by reference.
Japanese patent application No. 087322 in 2017 (filed on Apr. 26, 2017)

1: driving control system, 2: vehicle, 10: surrounding environment recognition device, 20: vehicle-mounted display control device, 30: own vehicle position determination device, 40: external sensor group, 50: vehicle sensor group, 60: map information management Device: 70: travel control device, 80: actuator group, 90: display device, 100: processing unit, 101: own vehicle information acquisition unit, 102: surrounding environment element acquisition unit, 103: environment element movement prediction unit, 104: existence Time range determining unit, 105: driving risk determining unit, 106: driving risk map creating unit, 107: driving risk map providing unit, 120: storage unit, 121: own vehicle information data group, 122: surrounding environment element information Data group, 123: Parameter data group, 124: Driving risk map data group, 130: Communication unit, 200: Processing unit, 201: Driving risk map acquisition unit, 202: Control plan information Obtaining unit, 203: traveling risk map display control unit, 220: storage unit, 230: communication unit, 240: display output unit

Claims

A surrounding environment recognition device that is mounted on a vehicle and recognizes the surrounding environment of the vehicle,
A host vehicle information acquisition unit for acquiring host vehicle information relating to the movement of the vehicle including a traveling speed of the vehicle;
A peripheral environment element acquisition unit that acquires peripheral environment element information for environmental elements around the vehicle;
A travel risk determining unit that determines the travel risk at a plurality of positions around the vehicle based on the vehicle information and the surrounding environment element information, and
The surrounding environment recognition device in which the interval between the plurality of positions in the front-rear direction of the vehicle changes according to the traveling speed of the vehicle.
The surrounding environment recognition apparatus according to claim 1,
The interval between the plurality of positions in the front-rear direction of the vehicle changes in proportion to the traveling speed of the vehicle when the traveling speed of the vehicle is greater than or equal to a predetermined value, and is constant when the traveling speed of the vehicle is less than the predetermined value. A surrounding environment recognition device.
In the surrounding environment recognition device according to claim 2,
When the traveling speed of the vehicle is less than the predetermined value, the surrounding environment recognition device increases the number of the plurality of positions behind the vehicle as the traveling speed of the vehicle decreases.
The surrounding environment recognition apparatus according to claim 1,
The surrounding environment recognition device in which the number of the plurality of positions is constant with respect to a change in travel speed of the vehicle.
The surrounding environment recognition apparatus according to claim 1,
The surrounding environment recognition device in which an interval between the plurality of positions in the lateral direction of the vehicle is constant with respect to a change in a traveling speed of the vehicle.
In the surrounding environment recognition device according to claim 5,
The surrounding environment recognition apparatus in which the interval between the plurality of positions in the lateral direction of the vehicle increases as the distance from the central axis that penetrates the vehicle in the front-rear direction increases.
The surrounding environment recognition apparatus according to claim 1,
A surrounding environment recognition device further comprising a travel risk level map creation unit that creates a travel risk level map representing a relationship between each of the plurality of positions and the travel risk level.
The surrounding environment recognition apparatus according to claim 1,
Based on the vehicle information, the vehicle presence time range representing the vehicle presence time range for each of the plurality of positions is determined, and based on the surrounding environment element information, An existence time range determination unit that determines an environment element existence time range that represents the existence time range of the environment element;
The driving risk determination unit is a surrounding environment recognition device that determines driving risk at the plurality of positions based on the vehicle existence time range and the environment element existence time range.
A display control device that displays information about the vehicle on a display device mounted on the vehicle,
A travel risk map acquisition unit for acquiring a travel risk map representing the travel risk at a plurality of positions around the vehicle;
A travel risk map display control unit that causes the display device to display the travel risk map acquired by the travel risk map acquisition unit;
A display control device in which a display target range of the travel risk map around the vehicle changes according to a travel speed of the vehicle.
The display control device according to claim 9,
The travel risk map is divided into a plurality of cells respectively corresponding to the plurality of positions,
The size of the cell in the travel risk map changes according to the travel speed of the vehicle when the travel speed of the vehicle is greater than or equal to a predetermined value, and is constant when the travel speed of the vehicle is less than the predetermined value. Display control device.
The display control apparatus according to claim 10,
A display control device that changes a position of the vehicle in the travel risk map according to a travel speed of the vehicle when the travel speed of the vehicle is less than the predetermined value.
The display control device according to claim 11,
When the travel speed of the vehicle is less than the predetermined value, the display control apparatus is such that the position of the vehicle approaches the center of the travel risk map as the travel speed of the vehicle decreases.
The display control device according to claim 9,
The travel risk map is divided into a plurality of cells respectively corresponding to the plurality of positions,
The travel risk map is represented on a time scale according to the arrival time of the vehicle when the travel speed of the vehicle is greater than or equal to a predetermined value, and the distance from the vehicle when the travel speed of the vehicle is less than the predetermined value. A display control device that is represented by a corresponding distance scale.