JP7391264B2 - Driving support device and driving support method - Google Patents

Description

The present disclosure relates to a driving support device and a driving support method that determine a road on which a vehicle is traveling.

Regarding driving support devices that support driving of a vehicle running on a road, there is a driving support device that outputs driving support information based on a high-precision map having road shape information for each lane and the current position of the vehicle. In such a driving support device, it is necessary to determine whether the own vehicle is traveling on a high-precision map road that is a road included in a high-precision map.

BACKGROUND ART Conventionally, a technology has been disclosed that supports driving of a vehicle by providing a normal precision map having road shape information for each road and a high precision map corresponding to the normal precision map (see, for example, Patent Document 1). A possible method is to use the technique disclosed in Patent Document 1 to determine whether or not the vehicle is traveling on a high-precision map road based on the current position of the vehicle and the normal-precision map.

Japanese Patent Application Publication No. 2006-266865

In order to make a judgment using the above method, it is necessary to maintain a normal precision map with a large amount of data. However, considering the cost of memory for storing normal precision maps, it is desirable to determine whether or not the vehicle is traveling on a high precision map road using a smaller amount of information.

The present disclosure has been made to solve such problems, and is a driving support device that can determine whether or not the own vehicle is traveling on a high-precision map road using a small amount of information. and related to driving support methods.

In order to solve the above problems, the driving support device according to the present disclosure includes a surrounding information acquisition unit that acquires surrounding information indicating the surrounding situation of the own vehicle from a surrounding detection device that detects the surrounding situation of the own vehicle, and a surrounding information acquisition unit that acquires surrounding information indicating the surrounding situation of the own vehicle. The surrounding information acquired by the surrounding information acquisition unit at a point where there is a high-precision map road that is a road included in a high-precision map having road shape information and a parallel road that runs parallel to the high-precision map road. This is information for comparing and determining whether the vehicle is traveling on a high-precision map road or a parallel road, and is information indicating the surrounding situation of the vehicle that has been detected by the surrounding detection device in advance. Based on the side-by-side running information storage unit that stores information, the surrounding information acquired by the surrounding information acquisition unit at the point , and the side-by-side running information at the point , the vehicle can determine whether it is traveling on a high-precision map road or a side-by-side road. The parallel road is a normal road that is included in a normal precision map having road shape information for each road .

According to the present disclosure, it is possible to determine whether the own vehicle is traveling on a high-precision map road using information with a small amount of data.

Objects, features, aspects, and advantages of the present disclosure will become more apparent from the following detailed description and accompanying drawings.

1 is a block diagram showing an example of a configuration of a driving support device according to a first embodiment; FIG. 1 is a block diagram showing an example of a configuration of a driving support device according to a first embodiment; FIG. 5 is a flowchart illustrating an example of the operation of the driving support device according to the first embodiment. FIG. 3 is a diagram for explaining determination of a road on which the own vehicle is traveling. FIG. 3 is a diagram for explaining determination of a road on which the own vehicle is traveling. FIG. 3 is a diagram for explaining determination of a road on which the own vehicle is traveling. FIG. 3 is a diagram for explaining parallel running information according to the first embodiment. FIG. 7 is a diagram for explaining parallel running information according to Embodiment 2. FIG. FIG. 7 is a diagram for explaining parallel running information according to Embodiment 3; FIG. 7 is a diagram for explaining parallel running information according to Embodiment 4; FIG. 12 is a diagram for explaining parallel running information according to Embodiment 5. FIG. FIG. 12 is a diagram for explaining parallel running information according to Embodiment 5. FIG. FIG. 12 is a diagram for explaining parallel running information according to a modification of the fifth embodiment. FIG. 7 is a diagram for explaining parallel running information according to Embodiment 6; FIG. 7 is a block diagram showing an example of the configuration of a driving support device according to a seventh embodiment. 12 is a flowchart illustrating an example of the operation of the driving support device according to Embodiment 7. 2 is a diagram showing an example of a hardware configuration of a driving support device according to Embodiments 1 to 7. FIG. 2 is a diagram showing an example of a hardware configuration of a driving support device according to Embodiments 1 to 7. FIG.

<Embodiment 1>
<Configuration>
FIG. 1 is a block diagram showing an example of the configuration of a driving support device 1 according to the first embodiment. Note that FIG. 1 shows the minimum necessary configuration of the driving support device according to the first embodiment.

The driving support device 1 includes a surrounding information acquisition section 2 and a driving road determination section 3. The driving support device 1 is mounted on a vehicle (hereinafter also referred to as "own vehicle").

The surrounding information acquisition unit 2 obtains surrounding information indicating the surrounding situation of the own vehicle. The driving road determining unit 3 determines the point where the own vehicle has a high-precision map road, which is a road included in a high-precision map having road shape information for each lane, and a parallel road running parallel to the high-precision map road. When the vehicle is running, the vehicle automatically detects the vehicle based on pre-stored parallel traveling information, which is information about high-precision map roads and parallel roads at that point, and surrounding information acquired by the surrounding information acquisition unit 2 at that point. To determine whether a vehicle is traveling on a high-precision map road or a parallel road.

Next, other configurations of the driving support device including the driving support device 1 shown in FIG. 1 will be described.

FIG. 2 is a block diagram showing an example of the configuration of the driving support device 4 according to another configuration.

The driving support device 4 includes a surrounding information acquisition section 2, a driving road determination section 3, a position information acquisition section 5, a road information output section 6, a high-precision map storage section 7, and a parallel driving information storage section 8. We are prepared. Further, the driving support device 4 is connected to a positioning device 9, a surroundings detection device 10, and an automatic driving control device 11. The driving support device 4, the positioning device 9, the surroundings detection device 10, and the automatic driving control device 11 are installed in the host vehicle.

Note that the driving support device 4 is a system that is not only an in-vehicle navigation device, that is, a car navigation device, but also a PND (Portable Navigation Device) that can be installed in the vehicle, a server installed outside the vehicle, etc. The present invention can also be applied to a constructed navigation device or a device other than a navigation device constructed as a system. In this case, each function or each component of the driving support device is distributed and arranged in each function that constructs the above system.

The surrounding information acquisition unit 2 obtains surrounding information from the surrounding detection device 10 that detects the surrounding situation of the own vehicle. The surrounding detection device 10 includes, for example, at least one of an image sensor, LiDAR (Light Detection and Ranging), an ultrasonic sensor, an acceleration sensor, a gyro sensor, and a communication device.

The position information acquisition unit 5 acquires current position information of the own vehicle from the positioning device 9. The positioning device 9 identifies the current position of the vehicle using GNSS (Global Navigation Satellite System). Furthermore, the positioning device 9 may specify the current position of the own vehicle by also considering detection results obtained from a gyro sensor, a vehicle speed sensor, etc. provided in the own vehicle. In this case, the gyro sensor may be a gyro sensor provided as the surrounding detection device 10.

The high-precision map storage unit 7 stores a high-precision map having road shape information for each lane. The road shape information for each lane indicates the road shape for each lane, and is road information with an error of about several centimeters. Generally, the road shape of a lane is expressed by the center line of the lane, but it is not limited to the center line of the lane. A high-precision map road included in a high-precision map is a road expressed by road shape information on a lane-by-lane basis.

The parallel running information storage unit 8 stores information regarding a high precision map road and a parallel road at a point where a high precision map road and a parallel road running parallel to the high precision map road exist. The parallel running information stored in the parallel running information storage section 8 corresponds to the surrounding information acquired by the surrounding information acquisition section 2. That is, the surrounding information acquired by the surrounding information acquisition section 2 from the surrounding detection device 10 is stored in the parallel running information storage section 8 as parallel running information. Note that the timing at which the parallel running information is stored in the parallel running information storage unit 8 is not only when the host vehicle first runs a point where a high precision map road and a parallel running road exist, but also when a predetermined period of time has elapsed. It may also be when the own vehicle travels the same point again after the time has elapsed. Details of the parallel running information will be described later.

When the own vehicle is traveling at a point where a high-precision map road and a parallel road exist, the traveling road determining unit 3 uses parallel traveling information at that point stored in advance in the parallel traveling information storage unit 8, Based on the surrounding information acquired by the surrounding information acquisition unit 2 at that point, it is determined whether the own vehicle is traveling on a high-precision map road or a parallel road.

ADAS (Advanced Driver Assistance Systems) or AD (Autonomous Driving) includes a surrounding detection device 10. The surrounding information, which is the detection result of the surrounding detection device 10, includes information on the presence or absence of a feature to be detected, information indicating the direction in which the feature exists, numerical information such as lane width, road network information, etc. The amount of data is much smaller than that of a normal precision map. By using such surrounding information, it becomes possible to determine whether the vehicle is traveling on a high-precision map road or a parallel road without increasing the amount of data.

When the traveling road determining unit 3 determines that the own vehicle is traveling on a high-precision map road, the road information output unit 6 automatically outputs a high-precision map including the high-precision map road on which the own vehicle is traveling as road information. Output to the operation control device 11. The automatic driving control device 11 executes automatic driving control of the own vehicle. Specifically, the automatic driving control device 11 uses the high-precision map obtained from the road information output unit 6, the current position of the own vehicle obtained from the positioning device 9, and the surrounding information obtained from the surrounding detection device 10. Then, at least one of acceleration, steering, and control of the own vehicle is executed. Although the example in FIG. 2 shows the automatic driving control device 11, the automatic driving control device 11 may be used if the device controls the own vehicle or provides driving support using a high-precision map, such as a navigation device that provides route guidance. Other devices may also be used.

<Operation>
FIG. 3 is a flowchart showing an example of the operation of the driving support device 4. As shown in FIG. When the engine of the own vehicle is turned on, the operation shown in FIG. 3 starts, and when the engine of the own vehicle is turned off, the operation shown in FIG. 3 is ended.

In step S11, the position information acquisition unit 5 acquires current position information of the host vehicle.

In step S12, the driving road determining unit 3 determines whether the own vehicle is on a high-precision map road based on the position information acquired by the position information acquisition unit 5 and the high-precision map stored in the high-precision map storage unit 7. Determine whether or not the vehicle is driving nearby. For example, if the current position of the vehicle is within 200 meters from the high-precision map road, the traveling road determination unit 3 determines that the vehicle is traveling near the high-precision map road. If the host vehicle is traveling near a high-precision map road, the process moves to step S13. On the other hand, if the host vehicle is not traveling near a high-precision map road, the process returns to step S11.

In step S13, the surrounding information acquisition unit 2 detects surrounding information from the surrounding detection device 10. Specifically, the surrounding information acquisition unit 2 acquires surrounding information at the point acquired by the position information acquisition unit 5.

In step S14, the driving road determination unit 3 determines whether or not there is a road parallel to the road on which the host vehicle is traveling, based on the surrounding information acquired by the surrounding information acquisition unit 2. If a parallel road exists, the process moves to step S15. On the other hand, if there is no parallel road, the process moves to step S17.

In step S15, the driving road determining unit 3 determines whether the host vehicle is traveling on a high-precision map road or It is determined which of the parallel roads the vehicle is traveling on. Specifically, the traveling road determining unit 3 determines whether the own vehicle is traveling on a high-precision map road or a parallel road, based on the parallel traveling information and surrounding information at the point acquired by the position information acquiring unit 5. to judge whether

In step S16, as a result of the determination by the driving road determination unit 3, if the host vehicle is traveling on a high-precision map road, the process moves to step S17. On the other hand, if the host vehicle is not traveling on a high-precision map road, the process returns to step S11.

In step S17, the road information output unit 6 outputs a high-precision map including the high-precision map road on which the own vehicle is traveling to the automatic driving control device 11 as road information.

<Determining the road the vehicle is traveling on>
As shown in FIG. 4, the road section from IC1 to IC2 on the main road is a high-precision map road included in the high-precision map. Note that IC indicates an interchange. In FIG. 4, if there is a parallel road running parallel to the road section from IC1 to IC2, whether the host vehicle V is traveling on the high-precision map road or the parallel road after passing IC1? need to be determined.

FIG. 5 shows a case where a normal road exists as a parallel road running parallel to the road section from IC1 to IC2 (high-precision map road). A normal road is a road included in a normal precision map that has road shape information for each road. In the example of FIG. 5, it is difficult to judge whether the vehicle is traveling on a high-precision map road or a normal road using only the high-precision map, but it can be determined if the normal-precision map is also used. However, in order to make this determination, it is necessary to have a normal precision map, which poses a problem in that the amount of data required for the determination increases.

In order to solve this problem, in the first embodiment, as shown in FIG. 6, parallel running information is used instead of the normal precision map, and after the own vehicle V passes IC1, the high precision map road or parallel running information is used. Determine which road the vehicle is traveling on. This makes it possible to make decisions using a smaller amount of data than when using a normal precision map.

<Parallel information>
As shown in FIG. 7, parallel running information will be described when a first road, which is a high-precision map road, and a second road, which is a normal road, run parallel to each other.

(1) When the parallel running information includes "there is a road on the left side of the first road" and "there is a road on the right side of the second road", the running road judgment unit 3 uses the parallel running information and the surrounding information acquisition unit 2 The road on which the vehicle is traveling is determined based on surrounding information (where other roads exist relative to the road the vehicle is traveling on). For example, when the surrounding information indicates that "there is another road on the left side of the road on which the vehicle is traveling," the traveling road determination unit 3 determines that the road on which the vehicle is traveling is the first road (highway). (accuracy map road). At this time, the second road corresponds to a parallel road.

(2) When the parallel road includes "the number of lanes on the first road is 2" and "the number of lanes on the second road is 1", the running road judgment unit 3 uses the parallel running information and the surrounding information acquisition unit 2 The road on which the vehicle is traveling is determined based on the surrounding information (the number of lanes on the road the vehicle is traveling on). For example, when the surrounding information indicates that "the number of lanes on the road on which the host vehicle is traveling is 2", the driving road determination unit 3 determines that the road on which the host vehicle is traveling is the first road (high-precision map road). It is determined that At this time, the second road corresponds to a parallel road.

(3) The above (1) and (2) may be combined. In other words, when the parallel driving information includes "There is a road on the left side of the first road, and the number of lanes on the first road is 2" and "There is a road on the right side of the second road, and the number of lanes on the second road is 1". The driving road determination unit 3 uses the parallel driving information and the surrounding information acquired by the surrounding information acquisition unit 2 (where other roads exist with respect to the road on which the own vehicle is traveling, and where the own vehicle is traveling). The road on which the host vehicle is traveling is determined based on the number of lanes on the road on which the vehicle is traveling. For example, when the surrounding information indicates that "another road exists on the left side of the road on which the host vehicle is traveling, and the number of lanes on the road the host vehicle is traveling on is 2", the traveling road determination unit 3 , it is determined that the road on which the host vehicle is traveling is the first road (high-precision map road). At this time, the second road corresponds to a parallel road.

Note that in (1) to (3) above, the positional relationship of each road is expressed in the left-right direction, but the present invention is not limited to this. For example, the positional relationship of each road may be expressed by direction. The same applies to other embodiments.

<Effect>
From the above, according to the first embodiment, it is possible to determine whether the host vehicle is traveling on a high-precision map road without using a normal-precision map. In other words, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road using information with a small amount of data.

In the example of FIG. 3, surrounding information is first acquired in step S13, then it is determined in step S14 whether or not there is a parallel road, and then the road on which the own vehicle is traveling is determined in step S15. Although the case has been described above, it is not limited to this. For example, first, it is determined whether or not there is parallel running information for a point corresponding to the current position of the own vehicle, and if there is parallel running information (that is, a parallel road exists), the surrounding detection device 10 sends the surrounding information. After obtaining the information, the road on which the host vehicle is traveling may be determined based on the parallel traveling information and surrounding information.

<Embodiment 2>
In the second embodiment, the parallel running information includes features that are detectable by the surrounding detection device 10 on one of the high-precision map road and the parallel road, and that are undetectable by the surrounding detection device 10 on the other; It is characterized by including road information of at least one of a sign and a sign. The other configurations and operations are the same as those in Embodiment 1, so detailed explanations will be omitted here.

The terrestrial features detected by the surrounding detection device 10 include, for example, structures such as walls that exist on the side of the road, and structures such as ceilings that exist above the road. The surroundings detection device 10 in the second embodiment is, for example, LiDAR, an ultrasonic sensor, or a combination thereof.

As shown in FIG. 8, parallel running information will be described when a first road, which is a high-precision map road, and a second road, which is a normal road, run parallel to each other.

When the parallel driving information includes "There is a guide sign above the first road" and "There is a regulation sign indicating the maximum speed on the left side of the second road", the driving road judgment unit 3 uses the parallel driving information and the surrounding area. The road on which the vehicle is traveling is determined based on the surrounding information acquired by the information acquisition unit 2 (whether or not there are any features, etc. around the road the vehicle is traveling on). For example, when the surrounding information indicates that "a guide sign exists above the road on which the vehicle is traveling," the traveling road determination unit 3 determines that the road on which the vehicle is traveling is the first road (high-precision road). map road). At this time, the second road corresponds to a parallel road.

From the above, according to the second embodiment, it is possible to determine whether the vehicle is traveling on a high-precision map road without using a normal-precision map. In other words, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road using information with a small amount of data.

<Embodiment 3>
Embodiment 3 is characterized in that the parallel running information includes gradient information of a high-precision map road and gradient information of a parallel running road. The other configurations and operations are the same as those in Embodiment 1, so detailed explanations will be omitted here. The surroundings detection device 10 in the third embodiment is, for example, an acceleration sensor, a gyro sensor, or a combination thereof.

As shown in FIG. 9, parallel running information will be described when a first road and a second road, which is an upper road, run parallel to each other in order to go from a lower road to an upper road.

When the parallel running information includes "the gradient of the first road is X%" and "the gradient of the second road is Y%", the running road judgment unit 3 uses the parallel running information and the information acquired by the surrounding information acquisition unit 2. The road on which the vehicle is traveling is determined based on surrounding information (how steep the road the vehicle is traveling on). For example, when the surrounding information indicates that "the slope of the road on which the host vehicle is traveling is It is determined that At this time, the second road corresponds to a parallel road.

From the above, according to the third embodiment, it is possible to determine whether the vehicle is traveling on a high-precision map road without using a normal-precision map. In other words, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road using information with a small amount of data.

<Embodiment 4>
Embodiment 4 is characterized in that the parallel running information includes curve information of a high-precision map road and curve information of a parallel running road. The other configurations and operations are the same as those in Embodiment 1, so detailed explanations will be omitted here. The surrounding detection device 10 in the fourth embodiment is, for example, LiDAR.

As shown in FIG. 10, parallel running information when a first road, which is a high-precision map road, and a second road, which is a normal road, run parallel to each other will be described.

When the parallel running information includes "the first road connects to a right-hand curve" and "the second road does not connect to a curve", the running road judgment unit 3 uses the parallel running information and the surrounding information acquisition unit 2 obtains the parallel running information. The road on which the vehicle is traveling is determined based on the surrounding information (whether or not the road the vehicle is traveling on connects to a curve). For example, when the surrounding information indicates that "the road on which the host vehicle is traveling connects to a curve," the driving road determination unit 3 determines that the road on which the host vehicle is traveling is the first road (high-precision map road). It is determined that At this time, the second road corresponds to a parallel road.

The surrounding area detection device 10 measures the curvature of the lane in which the host vehicle is traveling, and compares the curvature of the parallel road stored as parallel travel information with the curvature of the high-precision map road to determine where the host vehicle is traveling. It may also be possible to determine whether the vehicle is traveling on a road. Further, the same judgment may be made when the parallel road is a straight line and the high-precision map road is curved, or when both are curved but with different curvatures. The parallel running information may include curvatures at locations where both the parallel running road and the high-precision map road have different curvatures.

From the above, according to the fourth embodiment, it is possible to determine whether the host vehicle is traveling on a high-precision map road without using a normal-precision map. In other words, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road using information with a small amount of data.

<Embodiment 5>
In the fifth embodiment, a description will be given of how the parallel running information described in the first to fourth embodiments is stored in the parallel running information storage section 8. Below, as an example, a case will be described in which parallel running information is stored in units of sublinks of a high-precision map road.

A sublink is a lane link representing the road shape of each lane of a high-precision map road, which is divided into sections having the same curvature. Each sublink has coordinates and curvature.

For example, the lane link L ₁₂ representing the road shape of IC1 to IC2 shown in FIG. 6 is expressed by a set of subnode coordinates n _m and curvature information _cm as shown in equation (1) below.
L ₁₂ = (n ₁ , c ₁ ) (n ₂ , c ₂ )...(n _M , c _M ) (1)

Further, the parallel running information ov _m is associated for each (n _m , _cm ), that is, for each sublink, as shown in equation (2) below.
L ₁₂ = (n ₁ , c ₁ , ov ₁ ) (n ₂ , c ₂ , ov ₂ )...(n _M , c _M , ov _M ) (2)

The parallel running information ov _m corresponds to the surrounding information acquisition unit detected by the surrounding detection device 10 at the subnode coordinates.

For example, as shown in FIG. 11, if the road on which the host vehicle is traveling has two lanes and there is a guide sign above the road, the surrounding information (image) detected by the surrounding detection device 10 (image sensor) It is divided into 16 parts, arranged in a line, and expressed in bit format. Specifically, when the image shown in FIG. 11 is expressed in bit format, the following equation (3) is obtained.
ov _m = a ₀ a ₁ a ₂ a ₃ a ₄ a ₅ a ₆ a ₇ a ₈ a ₉ a ₁₀ a ₁₁ a ₁₂ a ₁₃ a ₁₄ a ₁₅ (3)

Note that in the example of FIG. 11, since there is a guide sign in area _a1 , it may be expressed as the following equation (4).
ov _m =0100 0000 0000 0000 (4)

Furthermore, by representing the parallel running information in a bit format array, conditional judgments may be made based on the logical product of a plurality of parallel running information. For example, assume that three items, road markings, guide signs, and speed regulation signs, are set as detection items. As shown in Figure 12, when there is a guide sign in area _a1 , a speed control sign in area _a8 , and no road markings, the locations (subnode coordinates) shown in Figure 12 are arranged. The running information ov _m is expressed as shown in equation (5) below.
ov _m [] = {{0000 0000 0000 0000},
{0100 0000 0000 0000},
{0000 0000 1000 0000}} (5)

In equation (5), "{0000 0000 0000 0000}" in the first row represents the presence or absence of a road marking (here, no road marking). "{0100 0000 0000 0000}" in the second row indicates the presence or absence of a guide sign (in this case, there is a guide sign). "{0000 0000 1000 0000}" in the third row indicates the presence or absence of a speed regulation sign (here, a speed regulation sign is present).

At the point (subnode coordinates) shown in FIG. 12, if the surrounding information having the same three detection items as above is dV _m , the result of the logical product of ov _m and dV _m is expressed by the following equation (6). If this happens, it can be determined that the vehicle is not driving on a high-precision map road.
Result={{0000 0000 0000 0000},
{0000 0000 0000 0000},
{0000 0000 0000 0000}} (6)

Note that a format such as the following equation (7) may be used.
ov _m = {0100 0000 0000 0000}, TYPE (7)

In equation (7), TYPE is a value indicating a feature attribute. For example, the TYPE of the guide sign is "01H", the TYPE of the side wall is "02H", and the TYPE of the speed limit is "03H". Further, an attribute value (VALUE) or the like may be added to TYPE. The attribute value is a specific speed limit value, a specific area name, or the like. Furthermore, the positional relationship of parallel roads, etc. may be expressed in an appropriate _ovm format.

From the above, according to the fifth embodiment, it is possible to determine whether the vehicle is traveling on a high-precision map road without using a normal-precision map. In other words, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road using information with a small amount of data.

<Modification of Embodiment 5>
In the fifth embodiment, a case has been described in which parallel running information is associated with each subnode coordinate, but the present invention is not limited to this. The parallel running information may be associated only with points where there is a parallel road running parallel to the high-precision map road.

For example, a case will be described in which the section IC1 to IC2 shown in FIG. 6 is represented by subnode coordinates n ₁ to n ₆ shown in FIG. 13. The lane link _L12 representing the road shape of IC1 to IC2 shown in FIG. 6 is expressed by the above equation (1). As shown in FIG. 13, when a parallel road exists near the subnode coordinates _n1 and _n5 , the lane link _L12 is expressed by the following equation (8).
L ₁₂ = (n ₁ , c ₁ ) (n ₂ , c ₂ )...(n _M , c _M ), ov (n ₁ , c ₁ ) ov (n ₅ , c ₅ ) (8)

As shown in Equation (8), ov(n _n , c _n ) is set as many times as there are subnode coordinates where parallel roads exist.

From the above, according to the modification of the fifth embodiment, it is possible to reduce the amount of data of the parallel running information stored in the parallel running information storage section 8.

<Embodiment 6>
In Embodiment 6, a case will be described in which two different high-precision map roads run parallel to each other. The configuration and operation are similar to those in Embodiment 1, so detailed description will be omitted here.

As shown in FIG. 14, parallel running information will be described when a first road, which is a high-precision map road, and a second road, which is a high-precision map road, are running parallel to each other.

When the parallel running information includes "there is a road on the left side of the first road", the driving road judgment unit 3 uses the parallel running information and the surrounding information acquired by the surrounding information acquisition unit 2 (that is, there is a road on the left side of the first road). The road on which the host vehicle is traveling is determined based on the location of other roads. For example, when the surrounding information indicates that "there is another road on the left side of the road on which the vehicle is traveling," the traveling road determination unit 3 determines that the road on which the vehicle is traveling is the first road (highway). (accuracy map road). At this time, the second road corresponds to a parallel road.

From the above, according to Embodiment 6, at a point where two high-precision map roads run parallel to each other, whether or not the own vehicle is traveling on a high-precision map road without using a normal-precision map is determined. can be judged. In other words, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road using information with a small amount of data.

<Embodiment 7>
FIG. 15 is a block diagram showing an example of the configuration of the driving support device 12 according to the seventh embodiment. As shown in FIG. 15, the driving support device 12 is configured to be able to communicate with the parallel running information distribution server 14 via the communication device 13. Since the other configurations are the same as those in Embodiments 1 to 6, detailed explanation will be omitted here.

The communication device 13 is mounted on the host vehicle and is communicably connected to the parallel running information distribution server 14. The communication device 13 transmits the peripheral information acquired by the peripheral information acquisition unit 2 to the parallel running information distribution server 14. At this time, the communication device 13 may associate surrounding information with the position information acquired by the position information acquisition unit 5 and transmit it to the parallel running information distribution server 14 . Further, upon receiving (downloading) the parallel running information distributed from the parallel running information distribution server 14 , the communication device 13 stores the parallel running information in the parallel running information storage section 8 .

The parallel running information distribution server 14 is provided outside the driving support device 12, and distributes parallel running information in response to a request from the driving support device 12. Note that the parallel running information distribution server 14 may store surrounding information received from a driving support device other than the driving support device 12 as parallel running information.

FIG. 16 is a flowchart showing an example of the operation of the driving support device 12. Note that steps S21, S22, and steps S24 to S28 in FIG. 16 correspond to steps S11 to S17 in FIG. 3, so their explanations are omitted here. Below, step S23 will be explained.

In step S23, the traveling road determining unit 3 instructs the communication device 13 to download the parallel running information at the current position of the host vehicle acquired by the position information acquiring unit 5. The communication device 13 requests the parallel running information distribution server 14 to distribute the parallel running information, and downloads the parallel running information. The downloaded parallel running information is stored in the parallel running information storage section 8.

From the above, according to the seventh embodiment, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road without using a normal-precision map. In other words, it is possible to determine whether or not the own vehicle is traveling on a high-precision map road using information with a small amount of data.

<Hardware configuration>
Each function of the surrounding information acquisition section 2, the driving road determination section 3, the position information acquisition section 5, and the road information output section 6 in the driving support device 4 described in the first embodiment is realized by a processing circuit. That is, the driving support device 4 acquires surrounding information, determines the road on which the own vehicle is traveling, acquires current position information of the own vehicle, and determines that the own vehicle is traveling on a high-precision map road. The system is equipped with a processing circuit for outputting road information including high-definition maps when The processing circuit may be dedicated hardware, and may be a processor (CPU, central processing unit, processing unit, arithmetic unit, microprocessor, microcomputer, DSP (Digital Signal Processor)) that executes a program stored in memory. ).

When the processing circuit is dedicated hardware, as shown in FIG. 17, the processing circuit 15 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, or an ASIC (Application Specific Integrated Circuit). , FPGA (Field Programmable Gate Array), or a combination of these. Each function of the surrounding information acquisition section 2, driving road determination section 3, position information acquisition section 5, and road information output section 6 may be realized by the processing circuit 15, respectively, or each function may be realized by a single processing circuit 15. It may be realized.

In the case where the processing circuit 15 is the processor 16 shown in FIG. This is realized in combination with firmware. Software or firmware is written as a program and stored in memory 17. The processor 16 implements each function by reading and executing programs recorded in the memory 17. That is, the driving support device 4 performs a step of acquiring surrounding information, a step of determining the road on which the own vehicle is traveling, a step of acquiring current position information of the own vehicle, and a step of determining the current position information of the own vehicle while the own vehicle is traveling on a high-precision map road. A memory 17 is provided for storing a program that results in the step of outputting road information including a high-precision map when it is determined that there is a high-precision map. It can also be said that these programs cause the computer to execute the procedures or methods of the surrounding information acquisition section 2, the traveling road determination section 3, the position information acquisition section 5, and the road information output section 6. Here, memory refers to nonvolatile or volatile memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), and EEPROM (Electrically Erasable Programmable Read Only Memory). The storage medium may be a flexible semiconductor memory, a magnetic disk, a flexible disk, an optical disk, a compact disk, a DVD (Digital Versatile Disc), or any storage medium that will be used in the future.

Note that some of the functions of the surrounding information acquisition unit 2, driving road determination unit 3, position information acquisition unit 5, and road information output unit 6 are realized by dedicated hardware, and other functions are realized by software or It may be realized by firmware.

In this way, the processing circuit can implement each of the above functions using hardware, software, firmware, or a combination thereof.

Although the hardware configuration of the driving support device 4 described in the first embodiment has been described above, the same applies to the hardware configuration of the driving support device 12 described in the seventh embodiment.

Note that within the scope of the present disclosure, it is possible to freely combine the embodiments, or to modify or omit each embodiment as appropriate.

Although the present disclosure has been described in detail, the above description is in all aspects illustrative and not restrictive. It is understood that countless variations not illustrated may be envisioned.

1 Driving support device, 2 Surrounding information acquisition unit, 3 Driving road determination unit, 4 Driving support device, 5 Position information acquisition unit, 6 Road information output unit, 7 High precision map storage unit, 8 Parallel driving information storage unit, 9 Positioning device, 10 peripheral detection device, 11 automatic driving control device, 12 driving support device, 13 communication device, 14 parallel running information distribution server, 15 processing circuit, 16 processor, 17 memory.

Claims (11)

a surrounding information acquisition unit that obtains surrounding information indicating the surrounding situation of the own vehicle from a surrounding detection device that detects the surrounding situation of the own vehicle;
Information acquired by the surrounding information acquisition unit at a point where there is a high-definition map road that is a road included in a high-definition map having road shape information for each lane and a parallel road that runs parallel to the high-definition map road. This is information for comparing with the surrounding information to determine whether the own vehicle is traveling on the high-precision map road or the parallel road, and is information that is used to determine whether the own vehicle is traveling on the high-precision map road or the parallel road. a parallel running information storage unit storing parallel running information that is information indicating surrounding conditions;
Based on the surrounding information acquired by the surrounding information acquisition unit at the point and the side-by-side information at the point, which of the high-precision map road or the side-by-side road the host vehicle is traveling on is determined. a driving road judgment unit that judges the
Equipped with
In the driving support device, the parallel road is a normal road that is included in a normal precision map having road shape information for each road. The parallel running information includes a positional relationship between the high precision map road and the parallel running road,
The surrounding information acquisition unit obtains the surrounding information including a positional relationship between the high-precision map road and the parallel road,
The traveling road determination unit determines whether the own vehicle is traveling on the high-precision map road or the parallel traveling road based on the positional relationship included in the parallel traveling information and the positional relationship included in the surrounding information. The driving support device according to claim 1, which determines whether the vehicle is running. The parallel running information includes features, signs, and signs that are detectable by the surrounding detection device on one of the high-precision map road and the parallel road, and that are undetectable by the surrounding detection device on the other. including road information for at least one of the markings;
The surrounding information acquisition unit obtains the surrounding information including road information of at least one of features, signs, and markings on the road on which the own vehicle is traveling,
The traveling road determination unit determines whether the own vehicle is traveling on the high-precision map road or the parallel traveling road based on the road information included in the parallel traveling information and the road information included in the surrounding information. The driving support device according to claim 1, which determines whether the vehicle is running. The parallel running information includes slope information of the high-precision map road and slope information of the parallel road,
The surrounding information acquisition unit obtains the surrounding information including slope information of the road on which the own vehicle is traveling,
The traveling road determining unit determines whether the host vehicle is traveling on the high-precision map road or the parallel traveling road based on the gradient information included in the parallel traveling information and the gradient information included in the surrounding information. The driving support device according to claim 1, which determines whether the vehicle is running. The parallel running information includes curve information of the high-precision map road and curve information of the parallel road,
The surrounding information acquisition unit obtains the surrounding information including curve information of a road on which the own vehicle is traveling,
The traveling road determining unit determines whether the own vehicle is traveling on the high-precision map road or the parallel traveling road based on the curve information included in the parallel traveling information and the curve information included in the surrounding information. The driving support device according to claim 1, which determines whether the vehicle is running. 2. The driving support device according to claim 1, wherein the parallel running information is associated with each sub-link obtained by dividing a lane link representing the road shape of each lane of the high-precision map road into sections having the same curvature. The driving support device according to claim 6, wherein the parallel running information is associated only with the sublink at the point. The driving support device according to claim 1, wherein the parallel road is another high-precision map road different from the high-precision map road. The driving support device according to claim 1, wherein the parallel running information is distributed from an external server. a road information output unit that outputs a high-precision map including the high-precision map road on which the own vehicle is traveling when the driving road determining portion determines that the own vehicle is traveling on the high-precision map road; The driving support device according to claim 1, further comprising: a driving support device according to claim 1; Obtaining surrounding information indicating the surrounding situation of the own vehicle from a surrounding detection device that detects the surrounding situation of the own vehicle,
A comparison is made with the acquired surrounding information at a point where a high-precision map road, which is a road included in a high-precision map having road shape information for each lane, and a parallel road running parallel to the high-precision map road exist. The information is for determining whether the host vehicle is traveling on the high-precision map road or the parallel road, and is information indicating the surrounding situation of the host vehicle detected in advance by the surrounding detection device. Memorize certain parallel running information,
determining whether the host vehicle is traveling on the high-precision map road or the parallel road, based on the surrounding information acquired at the point and the parallel running information at the point;
In the driving support method, the parallel road is a normal road that is included in a normal precision map having road shape information for each road.

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