JP2021068315A - Estimation method and estimation system of lane condition - Google Patents

Abstract

To provide an estimation method and an estimation system of a lane condition capable of estimating an obstacle even when a vehicle is queuing due to the obstacle that blocks the lane.SOLUTION: An objection detection sensor 10 mounted on a vehicle 1 detects a position of an object around the vehicle 1 (S1, S2), based on the detection result of the object detection sensor 10, a queue section 206 in which the vehicle queue is generated in a targeted lane 201 around the vehicle 1 is detected (S3), a vehicle speed of the vehicle in the queue section 206 is measured (S4), based on the detection result of the object detection sensor 10, a travelable section 207 in which the vehicle can travel at a first predetermined speed or higher is detected in a front section, which is a section ahead of the queue in the traveling direction of the targeted lane 201, is detected (S5), and when the speed of the vehicle in the queuing section 206 is equal to or less than a second predetermined speed lower than the first predetermined speed and a travelable section 207 is detected, it is estimated that an obstacle 203 blocking at least a part of the targeted lane 201 occurs.SELECTED DRAWING: Figure 5

Description

The present invention relates to an estimation method and an estimation system for the state of the lane in which the vehicle travels.

Patent Document 1 discloses a technique of transmitting information on a parked vehicle detected by the own vehicle to a management server, and the management server plots the existence of the parked vehicle on a map to provide street parking map information ( For example, Patent Document 1). When the own vehicle changes lanes in order to overtake the other vehicle, the own vehicle determines the other vehicle as a parked vehicle.

Japanese Unexamined Patent Publication No. 2015-76074

According to the technique described in Patent Document 1, a parked vehicle cannot be detected unless the vehicle transmitting the parked vehicle information changes lanes for overtaking the parked vehicle.
Therefore, if a parked vehicle is blocking the lane and a vehicle queue is generated in front of it, the parked vehicle is parked until the vehicle that transmits the parked vehicle information changes lanes to overtake the parked vehicle. There was a problem that the recognition of the parked vehicle was delayed because it could not be detected.
The present invention has been made by paying attention to the above-mentioned problems, and an object of the present invention is to make it possible to estimate the obstacle even when a vehicle queue is generated due to an obstacle blocking the lane. And.

In the lane state estimation method according to one aspect of the present invention, the position of an object around the vehicle is detected by an object detection sensor mounted on the vehicle, and the target lane around the vehicle is determined based on the detection result of the object detection sensor. The section in which the lane is generated is detected, the vehicle speed of the vehicle in the lane is measured, and the section ahead of the lane in the traveling direction based on the detection result of the object detection sensor. In the front section, a travelable section in which the vehicle can travel at a speed equal to or higher than the first predetermined speed is detected, and the speed of the vehicle in the queue section is equal to or less than the second predetermined speed lower than the first predetermined speed and the travelable section is defined. If detected, it is presumed that there is an obstacle blocking at least part of the target lane.

The obstacle can be estimated even when the vehicle is queuing due to an obstacle that blocks the lane.

It is a schematic block diagram of an example of the lane state estimation system of 1st Embodiment. It is explanatory drawing of an example of the lane state estimation method of 1st Embodiment. It is explanatory drawing of an example of the lane state estimation method of 1st Embodiment. It is explanatory drawing of an example of the lane state estimation method of 1st Embodiment. It is explanatory drawing of an example of the lane state estimation method of 1st Embodiment. It is explanatory drawing of an example of the lane state estimation method of 1st Embodiment. It is a block diagram of an example of the functional structure of the lane state estimation system of 1st Embodiment. It is a flowchart of an example of the lane state estimation method of 1st Embodiment. It is explanatory drawing of an example of the data transfer sequence in the lane state estimation system of 1st Embodiment. It is explanatory drawing of an example of the correction method of the obstacle existence section in the lane state estimation method of 2nd Embodiment. It is explanatory drawing of an example of the correction method of the obstacle estimation result in the lane state estimation method of 2nd Embodiment. It is explanatory drawing of an example of the correction method of the obstacle estimation result in the lane state estimation method of 2nd Embodiment. It is a schematic block diagram of an example of the lane state estimation system of 2nd Embodiment. It is a block diagram of an example of the functional configuration of the lane state estimation system of the second embodiment. It is a flowchart of an example of the lane state estimation method of 2nd Embodiment. It is explanatory drawing of an example of the lane state estimation method of 3rd Embodiment. It is a schematic block diagram of an example of the lane state estimation system of 3rd Embodiment. It is a block diagram of an example of the functional configuration of the lane state estimation system of the third embodiment. It is a flowchart of an example of the lane state estimation method of 3rd Embodiment.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the description of the drawings, the same or similar parts are designated by the same or similar reference numerals, and duplicate description will be omitted. Each drawing is schematic and may differ from the actual one. The embodiments shown below exemplify devices and methods for embodying the technical idea of the present invention, and the technical idea of the present invention is specified to the devices and methods exemplified in the following embodiments. Not something to do. The technical idea of the present invention can be modified in various ways within the technical scope described in the claims.

(First Embodiment)
(Constitution)
See FIG. The lane state estimation system 100 of the first embodiment acquires information on objects around the first vehicle 1 as probe information, and is a lane around the first vehicle 1 (hereinafter referred to as "target lane"). Estimate the state. The lane state estimation system 100 includes an object detection sensor 10, a positioning device 11, a communication device 12, and computers 4, 5 and 6 mounted on the first vehicle 1.
FIG. 1 shows a second vehicle 2 that utilizes the estimation result of the target lane by the lane state estimation system 100. The second vehicle 2 includes an object detection sensor 20, a positioning device 21, a communication device 22, an in-vehicle device 23, and an actuator 24.

The object detection sensor 10 includes a plurality of different types of sensors that detect objects around the first vehicle 1.
For example, the object detection sensor 10 includes a camera mounted on the first vehicle 1. The object detection sensor 10 includes, for example, one or a plurality of cameras that image the surroundings of the first vehicle 1. The object detection sensor 10 includes, for example, a 4K resolution camera with a 90-degree angle of view that images the front of the first vehicle 1, a 4K resolution camera with a 90-degree angle of view that images the rear of the first vehicle 1, and the first vehicle 1. A 4K resolution camera having an angle of view of 180 degrees that images the left side of the first vehicle 1 and a 4K resolution camera having an angle of view of 180 degrees that images the right side of the first vehicle 1 may be provided.

The object detection sensor 10 of the first vehicle 1 acquires an image captured by each camera while synchronizing these cameras to image a range of 360 degrees around the first vehicle 1.
Further, for example, the object detection sensor 10 includes a range-finding sensor such as a laser radar, a millimeter-wave radar, or a LIDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging), and an object in front, behind, or side of the first vehicle 1. Road white line, road surface position data or point cloud data may be acquired.

The positioning device 11 includes a global positioning system (GNSS) receiver, receives radio waves from a plurality of navigation satellites, and measures the current time, the current position of the first vehicle 1, and the traveling direction. The GNSS receiver may be, for example, a Global Positioning System (GPS) receiver or the like. The positioning device 11 may be, for example, an inertial navigation system, or may measure the current position and the traveling direction of the first vehicle 1 by odometry.
The communication device 12 distributes the reference time to the object detection sensor 10 based on the current time information obtained from the positioning device 11. Further, the communication device 12 exchanges data with the object detection means 41 via the communication means 40 of the computer 4.

The object detection sensor 20 of the second vehicle 2 includes a plurality of different types of sensors that detect objects around the second vehicle 2. The object detection sensor 20 may include a camera mounted on the second vehicle 2 and a distance measuring sensor such as a laser radar, a millimeter wave radar, or LIDAR.
The positioning device 21 includes a global positioning system (GNSS) receiver, receives radio waves from a plurality of navigation satellites, and measures the current time, the current position of the second vehicle 2, and the traveling direction. The GNSS receiver may be, for example, a Global Positioning System (GPS) receiver or the like. The positioning device 21 may be, for example, an inertial navigation system, or may measure the current position and the traveling direction of the second vehicle 2 by odometry.

The communication device 22 receives the state information of the target lane from the obstacle section estimation means 61 via the communication means 60 of the computer 6.
The in-vehicle device 23 is an electronic control unit (ECU) that controls the traveling of the second vehicle 2. For example, the in-vehicle device 23 performs automatic driving control for automatically driving the second vehicle 2 based on the current position of the second vehicle 2 and the surrounding environment without the driver's involvement.

Further, for example, the in-vehicle device 23 performs driving support control that controls only steering or acceleration / deceleration of the second vehicle 2 based on the surrounding environment.
The in-vehicle device 23 includes a processor and peripheral parts such as a storage device. The processor may be, for example, a CPU (Central Processing Unit) or an MPU (Micro-Processing Unit). The storage device may include a semiconductor storage device, a magnetic storage device, an optical storage device, and the like. The storage device may include a memory such as a register, a cache memory, a ROM (Read Only Memory) and a RAM (Random Access Memory) used as the main storage device.

The actuator 24 operates the steering wheel, accelerator opening degree, and brake device of the second vehicle 2 in response to the control signal from the vehicle-mounted device 23 to generate the vehicle behavior of the second vehicle 2. The actuator 24 includes a steering actuator, an accelerator opening actuator, and a brake control actuator. The steering actuator controls the steering direction and steering amount of the steering of the second vehicle 2. The accelerator opening actuator controls the accelerator opening of the second vehicle 2. The brake control actuator controls the braking operation of the brake device of the second vehicle 2.

The computer 4 includes a communication means 40 and operates as an object detection means 41 described later. The computer 5 includes a communication means 50, and operates as a queue section detecting means 51, a speed determining means 52, and a travelable section detecting means 53, which will be described later. The computer 6 includes a communication means 60 and operates as a failure section estimation means 61 described later. The communication means 40, 50 and 60 can exchange data with each other by a wired or wireless communication means.

Computers 4 to 6 may be mounted on the first vehicle 1, for example. In this case, the communication device 12 and the communication means 40 to 60 may exchange data by a wired or wireless communication means. For example, the communication device 12 and the communication means 40 to 60 may include an in-vehicle communication network (in-vehicle LAN) such as a CSMA / CA type multiplex communication (CAN: Controller Area Network) or Flex Ray.
In this case, the communication device 22 and the communication means 60 of the second vehicle 2 may exchange data via wireless communication means such as vehicle-to-vehicle communication, public mobile phone network, road-to-vehicle communication, and satellite communication.

Further, the computers 4 to 6 may be mounted on the second vehicle 2, for example. In this case, the communication device 22 and the communication means 40 to 60 may exchange data by a wired or wireless communication means. For example, the communication device 22 and the communication means 40 to 60 may include an in-vehicle communication network (in-vehicle LAN) such as a CSMA / CA type multiplex communication or a flex ray.
In this case, the communication device 12 and the communication means 40 of the first vehicle 1 may exchange data via wireless communication means such as vehicle-to-vehicle communication, public mobile phone network, road-to-vehicle communication, and satellite communication.

The computers 4 to 6 may be mounted in a place other than the first vehicle 1 and the second vehicle 2. In this case, for example, the communication device 12 and the communication means 40, and the communication device 22 and the communication means 60 exchange data with each other via wireless communication means such as vehicle-to-vehicle communication, public mobile phone network, road-to-vehicle communication, and satellite communication. To do. Computers 4 to 6 may be implemented, for example, in another vehicle, a mobile edge computer on a mobile phone / self-employed network, a road transportation infrastructure server installed on the roadside, or a cloud server on the Internet.

Subsequently, an outline of the lane state estimation method by the lane state estimation system 100 of the first embodiment will be described.
See FIG. 2A. The road 200 is provided with a target lane 201 and an oncoming lane 202 adjacent to the target lane 201. The lane state estimation system 100 estimates the lane state of the target lane 201 in which the second vehicle 2 is traveling, based on the detection result of an object around the first vehicle 1 traveling in the oncoming lane 202.

Now, a part of the target lane 201 is blocked by the obstacle 203, and the vehicles 204a to 204c waiting for the turn of the lane change to pass the obstacle 203 behind the obstacle 203 in the traveling direction of the target lane 201. Suppose a column is occurring. The obstacle 203 may be, for example, a stationary object such as a parked vehicle parked in the target lane 201, or may be a construction section.
The obstacle 203 is not limited to a tangible object, and may be a blockade of a part of the target lane 201. The obstacle 203 may be, for example, a defect in the target lane 201. In the following example, the obstacle 203 will be described as a tangible object (stationary object).

The object detection sensor 10 of the first vehicle 1 detects the position of an object around the first vehicle 1 at the point P1. In the example of FIG. 2A, the object detection sensor 10 detects the obstacle 203 and the positions of the vehicles 204a to 204c on the target lane 201.
Further, the object detection sensor 10 detects the position of the lane boundary line (for example, the white road line) 205 of the target lane 201. The lane boundary line 205 is the opposite side of the object detection sensor 10 across the target lane 201 when the object detection sensor 10 is located at a point P1 on one side of the target lane 201 (that is, on the opposite lane 202 side). It is a lane boundary line representing the lane boundary of.

See FIG. 2B. When the time advances by the measurement interval T and the first vehicle 1 reaches the point P2, the object detection sensor 10 detects an object around the first vehicle 1 at the point P2. In the example of FIG. 2B, the object detection sensor 10 detects the positions of the obstacle 203, the vehicles 204a to 204c, and the lane boundary line 205.
The lane state estimation system 100 detects the distance between objects on the target lane 201 based on the detection result of the object detection sensor 10 at the point P2, and a lane is generated in the target lane 201 based on the distance between the objects. Detects a queue section 206 that may be in the vehicle queue.
In addition, in this specification, the term "section" is used to express the range of the target lane 201 in the direction of travel.

The lane state estimation system 100 detects the speeds of obstacles 203, vehicles 204a to 204c, which are objects in the queue section 206, based on the detection results of the object detection sensors 10 at points P1 and P2. The lane state estimation system 100 determines that the vehicles 204a to 204c traveling at the second predetermined speed or lower are "waiting vehicles".
See FIG. 2C. The lane state estimation system 100 is a section ahead of the lane in the traveling direction of the target lane 201 based on the detection result of the object detection sensor 10 at the point P2 (may be the detection result of the object detection sensor 10 at the point P2). In the front section, the travelable section 207 in which the vehicle can travel at the first predetermined speed or higher is detected.
For example, the lane state estimation system 100 may detect a section in which the lane boundary line 205 is continuously detected over a length of a predetermined length or more in the front section as a travelable section 207.

See FIG. 2D. In the lane state estimation system 100, in the queue section 206, the obstacle existence section 208, which is the section where the obstacle 203 is estimated to exist, and the quasi-stationary object existence section, which is the section in which the vehicle travels at a speed equal to or lower than the second predetermined speed. 209 and is estimated.
For example, the lane state estimation system 100 estimates a section occupied by a stationary object having a speed of 0 as an obstacle existing section 208.

When a stationary object having a speed of 0 is not detected, it has the same length as the queue section 206 as shown in FIG. 3, and the boundary position between the queue section 206 and the travelable section 207 is at the center. The interval is set as the fault-existing interval 208.
Further, the lane state estimation system 100 determines the section from the position farthest from the obstacle existence section 208 to the obstacle existence section 208 among the waiting vehicles 204a to 204c as the quasi-stationary object existence section 209.

As described above, according to the lane state estimation system 100 of the first embodiment, the travelable section 207 in which the vehicle can travel at the first predetermined speed or higher and the speed of the vehicle in the queuing section 206 are equal to or lower than the second predetermined speed. Based on this, it can be estimated that there is an obstacle 203 that blocks at least a part of the target lane 201.
Therefore, even if the obstacle 203 cannot be recognized in the state where the vehicle queue is generated due to the obstacle 203, the existence of the obstacle 203 that blocks the target lane 201 can be estimated.

Next, the functional configuration of the lane state estimation system 100 of the first embodiment will be described. FIG. 4 is a block diagram of an example of the functional configuration of the lane state estimation system 100 of the first embodiment.
The lane state estimation system 100 includes an object detection sensor 10, a positioning device 11, an object detection means 41, a queue section detection means 51, a speed determination means 52, a travelable section detection means 53, and an obstacle section estimation means. It includes 61, an orbit generating means 25, a traveling control means 26, and an actuator 24. The in-vehicle device 23 of the second vehicle 2 operates as the track generating means 25 and the traveling control means 26.

The object detection sensor 10 measures the position of an object around the first vehicle 1. For example, in the object detection sensor 10, the laser range finder measures the position of an object around the road of about 150 m in a line-of-sight range of a horizontal angle of 360 degrees around the first vehicle, and outputs a point cloud format detection result. In addition, the visible camera outputs image data of objects around the road.
The positioning device 11 measures the current position of the first vehicle 1 in a common coordinate system (for example, a world coordinate system or a map coordinate system) based on predetermined coordinates.

The object detection means 41 detects the position of an object around the first vehicle 1 based on the detection result of the object detection sensor 10. For example, the object detection means 41 clusters the point clouds output by the object detection sensor 10 to generate a cluster of point cloud data, thereby generating obstacles 203, vehicles 204a to 204c, and lanes, which are objects around the first vehicle 1. The boundary line 205 and its position are detected.
Further, the object detection means 41 detects the obstacle 203, the vehicles 204a to 204c, the lane boundary line 205 and their positions by analyzing the image data output by the object detection sensor 10.

The object detection means 41 converts the coordinate system of the positions of the objects around the first vehicle 1 into a common coordinate system based on the current position of the first vehicle 1. Alternatively, it may be expressed by the distance from a reference point such as an intersection on a high-precision map.
Further, the object detecting means 41 measures the change between the position of the object detected from the detection result of the object detection sensor 10 at the point P1 and the position of the object detected from the detection result of the object detection sensor 10 at the point P2. Based on the interval T, the speed and the moving direction of the obstacle 203 and the vehicles 204a to 204c are measured.

The queue section detecting means 51 detects a queue section 206 in which a vehicle line is generated in the target lane 201 and may be a queue of vehicles. For example, the queue section detecting means 51 detects a section in which the distance between objects on the target lane 201 is equal to or less than a predetermined threshold value as the queue section 206. For example, a section in which the inter-vehicle time is 3 seconds or less or the inter-vehicle distance is 30 m or less may be detected as the queue section 206.

The velocity determining means 52 determines the velocity of the object in the queue section 206 based on the velocity of the object measured by the object detecting means 41. In the example of FIG. 2A, the speeds of the obstacle 203 and the vehicles 204a to 204c in the queue section 206 are determined.
The speed determination means 52 determines that the vehicles 204a to 204c traveling at the second predetermined speed or lower are "waiting vehicles". The second predetermined speed may be set to, for example, half or less of the first predetermined speed.

The travelable section detecting means 53 detects a travelable section 207 in which the vehicle can travel at a first predetermined speed or higher in a front section which is a section ahead of the queue in the traveling direction of the target lane 201.
For example, the travelable section detecting means 53 sets an evaluation section for determining whether or not the travelable section 207 is a travelable section 207 in the front section.

The range of the evaluation section is a range from both ends of the queue section 206 to a point separated by a predetermined evaluation section length from the front end which is the front side with respect to the traveling direction of the target lane 201. The evaluation section length is set based on, for example, the assumed speed of the vehicle traveling in the target lane 201 and the predetermined head time. For example, the assumed speed of the vehicle traveling in the target lane 201 may be set to 40 km / h, the head time may be set to 5 seconds, and the evaluation section length may be set to 50 m.

The travelable section detecting means 53 detects the section in which the lane boundary line 205 is continuously detected by the object detection sensor 10 over a predetermined length (for example, 30 m) or more in the evaluation section as the travelable section 207. Good.
Further, for example, in the evaluation section, a section in which a background object such as a target existing outside the lane boundary line 205 is continuously detected by the object detection sensor 10 for a length equal to or longer than a predetermined length can be traveled. It may be detected as 207.

The background object existing outside the lane boundary line 205 is a target when the object detection sensor 10 is located at points P1 and P2 on one side of the target lane 201 (that is, on the opposite lane 202 side). It is a background object located on the other side of the lane 201 (that is, on the side opposite to the object detection sensor 10 with the target lane 201 in between). The background object may be, for example, a road structure, a curb, or a building around the road.

Further, the travelable section detecting means 53 may detect the section in which the vehicle is traveling at the first predetermined speed in the evaluation section as the travelable section 207.
On the other hand, when there is a vehicle traveling at the second predetermined speed in the evaluation section, the travelable section detecting means 53 moves the front end of the queue section 206 to the position of the vehicle and moves the queue section 206 to the position of the vehicle. It may be stretched.

The obstacle section estimation means 61 determines whether or not the speed of the vehicles 204a to 204c in the queue section 206 is equal to or lower than the second predetermined speed and the travelable section 207 is detected. When the speed of the vehicles 204a to 204c in the queue section 206 is equal to or less than the second predetermined speed and the travelable section 207 is detected, the obstacle section estimation means 61 has an obstacle 203 in the queue section 206. Then, the obstacle existence section 208, which is the estimated section, is estimated.

When a stationary object having a speed of 0 is detected in the queue section 206, the obstacle section estimating means 61 estimates the section occupied by the stationary object as the obstacle existing section 208. When a stationary object having a speed of 0 is not detected, it has the same length as the queue section 206 as shown in FIG. 3, and the boundary position between the queue section 206 and the travelable section 207 is at the center. The section is set as the failure existing section 208.

Further, the obstacle section estimation means 61 estimates the quasi-stationary object existence section 209, which is a section in which the vehicle travels at a speed equal to or lower than the second predetermined speed in the queue section 206. The obstacle section estimation means 61 determines the section from the position farthest from the obstacle existence section 208 to the obstacle existence section 208 among the waiting vehicles 204a to 204c as the quasi-stationary object existence section 209.
The obstacle section estimation means 61 transmits the position information of the obstacle existing section 208 to the in-vehicle device 23 of the second vehicle 2.

The track generating means 25 of the in-vehicle device 23 generates a target traveling track and a speed profile for traveling the second vehicle 2 in the automatic traveling control or the driving support control of the second vehicle 2.
When the obstacle section estimation means 61 outputs the position information of the obstacle existence section 208 in front of the course of the second vehicle 2, the target traveling track and the speed profile are generated so as to avoid the obstacle existence section 208. Specifically, a target traveling track and a speed profile for changing lanes to the oncoming lane 202 in order to overtake the obstacle existing section 208 and changing lanes to the target lane 201 after overtaking the obstacle existing section 208 are generated.

The travel control means 26 drives the actuator 24 so that the second vehicle 2 travels on the target travel trajectory at a speed according to the speed profile generated by the track generation means 25. As a result, the actuator 24 performs steering control and acceleration / deceleration control so as to change lanes to the oncoming lane 202 in order to overtake the obstacle existing section 208, and to change lanes to the target lane 201 after overtaking the obstacle existing section 208.

As a result, even if the second vehicle 2 traveling behind the waiting vehicles 204a to 204c cannot recognize the obstacle 203 blocking the target lane 201 in front of the second vehicle 2, the obstacle 203 exists. The existence section 208 can be estimated in advance. As a result, it is possible to generate a vehicle behavior that avoids the obstacle existing section 208 with a margin without waiting for the recognition of the obstacle 203 and the determination of the size.
The in-vehicle device 23 may notify the driver or occupant of the second vehicle 2 of the obstacle existing section 208 and its position information as voice information or visual information.

(motion)
Next, an example of the lane state estimation method of the first embodiment will be described with reference to FIG.
In step S1, the object detection sensor 10 of the first vehicle 1 measures the positions of obstacles 203, vehicles 204a to 204c, and lane boundary line 205, which are objects around the first vehicle 1, at the point P1. The object detection means 41 detects these objects and their positions based on the detection result of the object detection sensor 10.

In step S2, the object detection sensor 10 of the first vehicle 1 measures the positions of the obstacle 203, the vehicles 204a to 204c, and the lane boundary line 205 at the point P2. The object detection means 41 detects these objects and their positions based on the detection result of the object detection sensor 10.
Further, the object detecting means 41 changes the position of the object detected from the detection result of the object detection sensor 10 at the point P1 and the position of the object detected from the detection result of the object detection sensor 10 at the point P2, and the measurement interval. Based on T, the speeds of obstacle 203 and vehicles 204a-204c are measured.

In step S3, the queue section detecting means 51 detects the queue section 206 in which a vehicle queue is generated in the target lane 201.
In step S4, the speed determination means 52 determines the speeds of the obstacle 203 and the vehicles 204a to 204c, which are the objects in the queue section 206, based on the speed of the object measured by the object detection means 41.
The speed determination means 52 determines that the vehicles 204a to 204c traveling at the second predetermined speed or lower are "waiting vehicles".

In step S5, the travelable section detecting means 53 detects the travelable section 207 in which the vehicle can travel at the first predetermined speed or higher in the front section which is the section ahead of the queue in the traveling direction of the target lane 201.
In step S6, the obstacle section estimation means 61 estimates the section occupied by the stationary object having a speed of 0 in the queue section 206 as the failure existence section 208.
The obstacle section estimation means 61 estimates the quasi-stationary object existence section 209, which is a section in which the vehicle travels at a speed equal to or lower than the second predetermined speed in the queue section 206.

Next, an example of the data transfer sequence in the lane state estimation system 100 will be described with reference to FIG.
At time t1, the object detection sensor 10 measures the positions of obstacles 203, vehicles 204a to 204c, and lane boundary line 205, which are objects around the first vehicle 1, at point P1. Further, the positioning device 11 measures the current position of the first vehicle 1. The object detection sensor 10 and the positioning device 11 add data transmission time information to the sensor signal (for example, point cloud data and image data) of the object detection sensor 10, the position data of the point P1, and the measurement time data to detect the object. It is transmitted to the means 41.

At time t2, the object detection means 41 receives these data. The object detection means 41 detects these objects and their positions based on the detection result of the object detection sensor 10.
After that, at the time t4 after the time t3, the object detection sensor 10 measures the position of the object around the first vehicle 1 at the point P2. The positioning device 11 measures the current position of the first vehicle 1. The time interval from time t1 to time t3 is set so that the measurement interval (interval from time t1 to t4) is longer than the time required to measure the velocity of the object from the change in the position of the object. There is.

The object detection sensor 10 and the positioning device 11 add data transmission time information to the sensor signal (for example, point cloud data and image data) of the object detection sensor 10, the position data of the point P1, and the measurement time data to detect the object. It is transmitted to the means 41.
At time t5, the object detection means 41 receives these data. The object detection means 41 detects these objects and their positions based on the detection result of the object detection sensor 10. Further, based on the change between the position of the object detected from the detection result of the object detection sensor 10 at the point P1 and the position of the object detected from the detection result of the object detection sensor 10 at the point P2, the obstacle 203 and the vehicle 204a Measure the speed of ~ 204c.

At time t6, the object detecting means 41 obtains the position information and speed of the obstacle 203 and the vehicles 204a to 204c and the position information of the lane boundary line 205 with the queuing section detecting means 51, the speed determining means 52, and the travelable section detecting means 53. Send to. At time t7, the queue section detecting means 51, the speed determining means 52, and the travelable section detecting means 53 receive these data.
The queue section detecting means 51 detects the queue section 206. The speed determination means 52 determines the speeds of the obstacle 203 and the vehicles 204a to 204c in the queue section 206. The travelable section detecting means 53 detects the travelable section 207.

At time t8, the queue section detecting means 51, the speed determining means 52, and the travelable section detecting means 53 obtain the data of the queue section 206, the speed of the object in the queue section 206, and the travelable section 207 as the obstacle section estimating means 61. Send to. At time t9, the fault interval estimation means 61 receives these data.
The obstacle section estimation means 61 estimates the obstacle existence section 208 and the quasi-stationary object existence section 209.

When the sensor signal of the object detection sensor 10 includes image data of a distant object (for example, one or more of the point groups for expressing the road boundary line is 30 m or more), uncompressed or lossless compression processing is performed. The data obtained by performing the above may be transmitted, and the compressed image may be transmitted with the identification information for decompression in the other image areas. In addition, the position coordinates may be expressed using the latitude and longitude handled by GNSS, the distance from the nearest intersection, and the plane orthogonal coordinate system (specified in the 2002 Ministry of Land, Infrastructure, Transport and Tourism Notification No. 9 and the like). As the time information, the time information distributed from GNSS may be used.

(Effect of the first embodiment)
(1) The object detection sensor 10 mounted on the first vehicle 1 detects the position of an object around the first vehicle 1. The queue section detecting means 51 detects the queue section 206 in which the vehicle queue is generated in the target lane 201 around the first vehicle 1 based on the detection result of the object detection sensor 10. The speed determination means 52 measures the vehicle speed of the vehicle in the queue section 206. Based on the detection result of the object detection sensor 10, the travelable section detecting means 53 is a travelable section in which the vehicle can travel at a first predetermined speed or higher in a front section which is a section ahead of the queue in the traveling direction of the target lane 201. 207 is detected. When the speed of the vehicle in the queue section 206 is equal to or less than the second predetermined speed lower than the first predetermined speed and the travelable section 207 is detected, the obstacle section estimation means 61 detects at least one of the target lanes 201. It is presumed that there is an obstacle 203 that closes the part.

Thereby, in a state where the vehicle queue is generated due to the obstacle 203, the existence of the obstacle 203 that blocks the target lane 201 can be estimated even if the obstacle 203 cannot be recognized.
Therefore, for example, even if the second vehicle 2 traveling behind the waiting vehicles 204a to 204c cannot recognize the obstacle 203 blocking the target lane 201 in front of the second vehicle 2, the obstacle 203 exists. The fault existence section 208 can be estimated in advance. As a result, it is possible to generate a vehicle behavior that avoids the obstacle existing section 208 with a margin without waiting for the recognition of the obstacle 203 and the determination of the size.

(2) When the object detection sensor 10 is located on one side of the target lane 201, the travelable section detecting means 53 has a predetermined length of the lane boundary line 205 representing the lane boundary on the opposite side of the target lane 201. The section continuously detected by the object detection sensor 10 over the above length is detected as the travelable section 207.
As a result, the travelable section 207 can be detected even if the vehicle actually traveling at the first predetermined speed or higher cannot be detected.

(3) When the object detection sensor 10 is located on one side of the target lane 201, the travelable section detecting means 53 has a length such that the target existing on the other side of the target lane 201 has a predetermined length or more. The section continuously detected by the object detection sensor 10 is detected as the travelable section 207.
The stable travelable section 207 can be detected based on the detection results of various targets, not limited to the lane boundary line 205. For example, even if the lane boundary line 205 or the road structure changes due to the development of the road infrastructure, the travelable section 207 can be detected robustly.

(4) The travelable section detecting means 53 detects a section in which the vehicle traveling in the front section is traveling at the first predetermined speed or higher as the travelable section.
As a result, the travelable section 207 can be detected based on the vehicle that actually travels at the first predetermined speed or higher.

(5) The obstacle section estimation means 61 is a quasi-stationary section in the queue section 206, which is a section in which the obstacle 203 is estimated to exist, and a section in which the vehicle travels at a speed equal to or lower than the second predetermined speed. The object existence section 209 is estimated. The obstacle existence section 208 is a section sandwiched between the quasi-stationary object existence section 209 and the travelable section 207.
Thereby, the obstacle existence section 208 can be specified based on the boundary between the section occupied by the stopped object in the queue section 206 and the section occupied by the vehicle traveling at a low speed.

(Second Embodiment)
Next, the second embodiment will be described. See FIG. 7. The lane state estimation system 100 of the second embodiment detects the lighting 210 of the direction indicator of the vehicle in the queue section 206.
When the vehicle in the queue section 206 lights the turn signal in the steering direction (that is, the oncoming lane 202 side) necessary for changing the lane overtaking the obstacle 203, the lane condition estimation system 100 performs such a direction instruction. The boundary position between the obstacle existing section 208 and the quasi-stationary object existing section 209 is changed to the position in front of the position of the frontmost vehicle among the vehicles in which the device is lit.
As a result, even if the waiting vehicles 204a to 204c are stopped, the section occupied by the waiting vehicles 204a to 204c can be excluded from the obstacle existing section 208, and the obstacle existing section 208 can be limited.

Further, the lane state estimation system 100 in the second embodiment estimates the characteristics of the queue of the vehicles 204a to 204c according to the position of the obstacle existence section 208, and estimates the obstacle existence section 208 according to the characteristics of the queue. cancel. That is, it is estimated that there is no obstacle 203 that blocks the target lane 201.
See FIG. Within the obstacle section 208, there are (a) a temporary stop line at the intersection, (b) a stop line at the intersection at the red light, (c) the end point of the curve, (d) the start point of the downhill slope, or (f) the parking lot. It is assumed that there is an entrance / exit of a facility along a full road. These points are referred to as "overtaking unnecessary points Pu1". The queue that occurs before the overtaking unnecessary point Pu1 is presumed to be a queue caused by a temporary stop or deceleration of the preceding vehicle.

In such a place, the vehicle speed may slow down even if the lane is not blocked, and the speed may recover when passing through the overtaking unnecessary point Pu1. Therefore, in this case, it is possible to pass through these points without changing lanes. The same applies when the overtaking unnecessary point Pu1 is (e) the head of the traffic jam.
Therefore, when such an overtaking unnecessary point Pu1 exists in the obstacle existence section 208, the estimation of the obstacle existence section 208 is canceled. As a result, automatic driving control or driving support control can be performed so as to suppress unnecessary lane changes.

Further, the lane state estimation system 100 in the second embodiment estimates the characteristics of the queue of the vehicles 204a to 204c according to the position of the quasi-stationary object existence section 209, and the obstacle existence section 208 according to the characteristics of the queue. Cancel the estimate. That is, it is estimated that there is no obstacle 203 that blocks the target lane 201.

See FIG. When (a) the end of the intersection queue, (b) the start point of the curve, (c) the start point of the uphill slope, or (d) the end point of the downhill slope exist in the start area of the quasi-stationary object existence section 209. Is assumed. These points are referred to as "overtaking unnecessary points Pu2".
The "starting area" of the quasi-stationary object existing section 209 is a predetermined distance forward from the rear end of both ends of the quasi-stationary object existing section 209, which is the rear side with respect to the traveling direction of the target lane 201. The range to a distant point.

The queue that occurs ahead of the overtaking unnecessary point Pu2 is presumed to be a queue caused by a temporary stop or deceleration of the preceding vehicle.
In such a place, the vehicle speed slows down even if the lane is not blocked, and if the vehicle passes the overtaking unnecessary point Pu2, the speed may eventually recover even if the speed temporarily slows down.

Therefore, in this case, it is possible to pass through these points without changing lanes. The same applies when the overtaking unnecessary point Pu2 is (e) the end of the traffic jam.
Therefore, when the overtaking unnecessary point Pu2 exists in the start area of the quasi-stationary object existence section 209, the estimation of the obstacle existence section 208 is canceled. As a result, automatic driving control or driving support control can be performed so as to suppress unnecessary lane changes.

(Constitution)
See FIG. The lane state estimation system 100 of the second embodiment includes a computer 7 in addition to the configuration of the lane state estimation system 100 of the first embodiment shown in FIG. The computer 7 includes a communication means 70, and operates as a turn signal detection means 71, a navigation system 72, and a queuing characteristic confirmation means 73.
The communication means 70 exchanges data with and from the object detection means 41 via the communication means 40 of the computer 4 by a wired or wireless communication means, and also communicates with the obstacle section via the communication means 60 of the computer 6. Data is exchanged with the estimation means 61.
The computer 7 may be mounted on the first vehicle 1 or the second vehicle 2, and is installed on a vehicle other than the first vehicle 1 or the second vehicle 2, a mobile edge computer on a mobile phone / self-employed network, or on the roadside. It may be implemented on a road transportation infrastructure server or a cloud server on the Internet.

The functional configuration of the lane state estimation system 100 of the second embodiment will be described with reference to FIG. The lane state estimation system 100 of the second embodiment has the same functional configuration as the lane state estimation system 100 of the first embodiment, and the same components are designated by the same reference numerals to provide duplicate explanations. Omit.
The object detection means 41 detects the lighting of the direction indicator of the object detected as a vehicle based on the image data output from the visible camera of the object detection sensor 10.

The direction indicator detecting means 71 determines whether or not the vehicle in which the direction indicator is lit is a vehicle in the queue section 206. Then, it is determined whether or not the vehicle lights the turn signal in the steering direction required for changing lanes overtaking the obstacle 203. The direction indicator detection means 71 outputs the determination result to the failure section estimation means 61.

When the vehicle in the queuing section 206 lights the turn signal in the steering direction required for changing lanes over the obstacle 203, the obstacle section estimation means 61 lights the turn signal in such a direction. The position of the frontmost vehicle 204c is determined. The obstacle section estimation means 61 changes the boundary position between the obstacle existence section 208 and the quasi-stationary object existence section 209 to the position in front of the vehicle 204c.

The navigation system 72 includes a map database that stores map information. Map information may be acquired from an external server via the communication means 70. Further, the navigation system 72 acquires road traffic information and parking lot full / empty information from an external server via the communication means 70.
The navigation system 72 detects the overtaking unnecessary points Pu1 and Pu2 based on the map information, the road traffic information, and the full sky information, and outputs them to the queuing characteristic confirmation means 73.

The queuing characteristic confirmation means 73 determines whether or not the overtaking unnecessary point Pu1 exists in the failure existence section 208 estimated by the failure section estimation means 61.
Further, the queuing characteristic confirmation means 73 determines whether or not there is an overtaking unnecessary point Pu2 in the start area of the quasi-stationary object existence section 209 estimated by the obstacle section estimation means 61. The queuing characteristic confirmation means 73 outputs the determination result to the failure section estimation means 61.

When the overtaking unnecessary point Pu1 exists in the obstacle existence section 208, or when the overtaking unnecessary point Pu2 exists in the start area of the quasi-stationary object existence section 209, the obstacle section estimation means 61 cancels the estimation of the obstacle existence section. ..
As a result, for example, since the position information of the obstacle existing section 208 is not output to the track generating means 25, the lane change for overtaking the obstacle existing section 208 is suppressed in the automatic traveling control or the driving support control of the second vehicle 2. ..

When the overtaking unnecessary point Pu1 is the entrance / exit of a facility along the road where the parking lot is full, the residence time of the object is determined in the obstacle existence section 208, and when the residence time is longer than the predetermined time, the obstacle existence section You may cancel the estimation of.
For example, when a plurality of vehicles having the same configuration as the first vehicle 1 travel in the oncoming lane 202, an object in the obstacle existing section 208 may be detected at different times to determine the residence time of the object.

Further, the failure section estimation means 61 may determine that the possibility that the failure 203 exists is low instead of canceling the estimation of the failure existence section. The track generating means 25 may determine whether or not it is necessary to change lanes in order to overtake the obstacle existing section 208, depending on the possibility that the obstacle 203 exists. For example, the track generating means 25 is required to change lanes in order to overtake the obstacle existing section 208 by combining other factors such as the risk existing around the second vehicle 2 in addition to the possibility that the obstacle 203 exists. You may decide whether or not.

Further, the obstacle section estimation means 61 may make it difficult to estimate that the obstacle 203 exists by increasing the first predetermined speed or decreasing the second predetermined speed instead of canceling the estimation of the obstacle existence section. In this case, the first predetermined speed or the second predetermined speed may be corrected according to the curve curvature at the overtaking unnecessary points Pu1 and Pu2 and the gradient rate.

(motion)
Next, an example of the lane state estimation method of the second embodiment will be described with reference to FIG.
The processing of steps S10 to S14 is the same as the processing of steps S1 to S5 of FIG.
In step S15, the turn signal detecting means 71 determines whether or not the vehicle in the procession section 206 lights the turn signal in the steering direction required for changing lanes overtaking the obstacle 203.

In step S16, the obstacle section estimation means 61 estimates the obstacle existence section 208 and the quasi-stationary object existence section 209. At this time, when the vehicle in the queuing section 206 turns on the turn signal in the steering direction necessary for changing the lane overtaking the obstacle 203, the obstacle section estimation means 61 sets the turn signal in such a direction. The position of the frontmost vehicle 204c among the lit vehicles is determined. The obstacle section estimation means 61 changes the boundary position between the obstacle existence section 208 and the quasi-stationary object existence section 209 to the position in front of the vehicle 204c.

In step S17, the queuing characteristic confirmation means 73 determines whether or not there is an overtaking unnecessary point Pu1 in the obstacle existence section 208. When the overtaking unnecessary point Pu1 does not exist in the obstacle existing section 208 (step S17: N), the process proceeds to step S18. When the overtaking unnecessary point Pu1 exists in the obstacle existing section 208 (step S17: Y), the process proceeds to step S19.

In step S18, the queuing characteristic confirmation means 73 determines whether or not there is an overtaking unnecessary point Pu2 in the start area of the quasi-stationary object existence section 209. When there is an overtaking unnecessary point Pu2 in the start area (step S18: Y), the process proceeds to step S19.
In step S19, the failure section estimation means 61 cancels the estimation of the failure existence section 208.

As a result, for example, the position information of the obstacle existing section 208 is not output to the track generating means 25, and the lane change for overtaking the obstacle existing section 208 is suppressed in the automatic traveling control or the driving support control of the second vehicle 2. ..
On the other hand, when the overtaking unnecessary point Pu2 does not exist in the start area in step S18 (step S18: N), the failure section estimation means 61 outputs the estimation of the failure section 208 without canceling the estimation. As a result, it is possible to change lanes for overtaking the obstacle existing section 208 in the automatic driving control or the driving support control of the second vehicle 2.

(Effect of the second embodiment)
(1) The direction indicator detecting means 71 detects a vehicle in which the direction indicator is lit in the queue section 206. The obstacle section estimation means 61 estimates that there is a boundary between the obstacle existence section 208 and the quasi-stationary object existence section 209 ahead of the vehicle in the traveling direction of the target lane 201.
As a result, even if the queue of vehicles is stopped in the queue section 206, the section occupied by these vehicles can be excluded from the obstacle existing section 208, and the obstacle existing section 208 can be limited.

(2) The queue characteristic confirmation means 73 queues according to the position of the obstacle existing section 208 or the position of the rear end of both ends of the quasi-stationary object existing section 209, which is the rear side with respect to the traveling direction of the target lane. Estimate the characteristics of. The fault section estimation means 61 estimates that the fault 203 does not exist according to the characteristics of the queue.
As a result, even though there is no obstacle 203 that blocks the target lane 201, if a queue is generated due to a temporary stop or deceleration of the preceding vehicle, it is erroneously determined that the obstacle 203 exists and is unnecessary. It is possible to prevent various lane changes.

(3) The obstacle section estimation means 61 estimates that the obstacle 203 does not exist when the intersection exists in the obstacle existence section 208.
As a result, even though there is no obstacle 203 that blocks the target lane 201, if the preceding vehicle temporarily stops or decelerates at the intersection and a queue is generated, it is erroneously assumed that the obstacle 203 exists. It is possible to prevent unnecessary lane changes by making a judgment.

(4) The obstacle section estimation means 61 determines the residence time of an object in the obstacle existence section 208 when there is an entrance / exit to a facility along the road in the obstacle existence section 208, and when the residence time is longer than a predetermined time, the obstacle It is estimated that 203 does not exist.
As a result, even though there is no obstacle 203 that blocks the target lane 201, an obstacle occurs when the preceding vehicle temporarily stops or decelerates at the entrance / exit to the facility along the road, causing a queue. It is possible to prevent an unnecessary lane change due to an erroneous determination that the 203 exists.

(5) The obstacle section estimation means 61 determines the obstacle 203 when the end point of the curve exists in the obstacle existence section 208 or the distance between the rear end of the quasi-stationary object existence section 209 and the start point of the curve is equal to or less than the threshold value. Is presumed to be nonexistent.
As a result, even though there is no obstacle 203 that blocks the target lane 201, if the preceding vehicle decelerates in the curve section and a queue is generated, it is erroneously determined that the obstacle 203 exists and is unnecessary. It is possible to prevent various lane changes.

(6) In the obstacle section estimation means 61, the starting point of the downward slope exists in the obstacle existing section 208, or the distance between the rear end of the quasi-stationary object existing section 209 and the starting point of the uphill or the ending point of the downward slope is If it is below the threshold, it is estimated that the failure 203 does not exist.
As a result, even though there is no obstacle 203 that blocks the target lane 201, if the preceding vehicle decelerates in the slope section and a queue is generated, it is erroneously determined that the obstacle 203 exists and is unnecessary. It is possible to prevent various lane changes.

(7) The obstacle section estimation means 61 has an obstacle 203 when the head of the traffic jam exists in the obstacle section 208 or the distance between the rear end of the quasi-stationary object existence section 209 and the tail of the traffic jam is equal to or less than the threshold value. I presume not.
As a result, it is possible to prevent an unnecessary lane change due to an erroneous determination that an obstacle 203 exists when there is a possibility that the speed will eventually recover after passing through a traffic jam.

(Third Embodiment)
Next, the third embodiment will be described. See FIG. In the lane state estimation system 100 of the third embodiment, the first vehicle 1 and the third vehicle are provided by the positioning devices mounted on each of the first vehicle 1 and the third vehicle 3 traveling in the oncoming lane 202 adjacent to the target lane 201. Measure each position of 3. Based on these measurement results, the distance between the first vehicle 1 and the third vehicle 3 is calculated.

Further, when an intermediate vehicle 220 having no self-position measuring and transmitting function is traveling between the first vehicle 1 and the third vehicle 3, the object detection sensor mounted on the first vehicle 1 enables the first operation. The first inter-vehicle distance D1 between the vehicle 1 and the intermediate vehicle 220 is detected. Further, the object detection sensor mounted on the third vehicle 3 detects the second inter-vehicle distance D2 between the third vehicle 3 and the intermediate vehicle 220. Further, the vehicle length L of the intermediate vehicle 220 is detected or estimated.
Further, based on the length of the queuing of the vehicles 204a to 204c and the speed limit of the target lane 201, the distance D3 required for the second vehicle 2 to change lanes to the oncoming lane 202 and overtake the obstacle 203 is calculated. Hereinafter, the distance D3 is referred to as "the required overtaking distance D3".

The total of the first inter-vehicle distance D1, the second inter-vehicle distance D2, and the vehicle length L matches the distance between the first vehicle 1 and the third vehicle 3, and the first inter-vehicle distance D1 is from the overtaking required distance D3. If it is long, it is determined that the second vehicle 2 can change lanes to the oncoming lane 202 and overtake the obstacle 203 at the timing when the first vehicle 1 passes by the side of the second vehicle 2.
Further, the total of the first inter-vehicle distance D1, the second inter-vehicle distance D2, and the vehicle length L matches the distance between the first vehicle 1 and the third vehicle 3, and the second inter-vehicle distance D2 is the required overtaking distance. If it is longer than D3, it is determined that the second vehicle 2 can change lanes to the oncoming lane 202 and overtake the obstacle 203 at the timing when the intermediate vehicle 220 passes by the side of the second vehicle 2.

When both the first inter-vehicle distance D1 and the second inter-vehicle distance D2 are equal to or less than the required overtaking distance D3, the timing at which the first vehicle 1 passes by the side of the second vehicle 2 and the intermediate vehicle 220 It is determined that the second vehicle 2 cannot overtake the obstacle 203 at any of the timings when the second vehicle 2 passes by the side of the second vehicle 2. In this case, the second vehicle 2 determines to stop before the obstacle 203.

If the total of the first inter-vehicle distance D1, the second inter-vehicle distance D2 and the vehicle length L does not match the distance between the first vehicle 1 and the third vehicle 3, the first inter-vehicle distance D1 or the second inter-vehicle distance Since it is considered that D2 has not been measured accurately, the second vehicle is at the timing when the first vehicle 1 passes by the side of the second vehicle 2 and when the intermediate vehicle 220 passes by the side of the second vehicle 2. 2 prohibits overtaking obstacle 203. In this case, the second vehicle 2 determines to stop before the obstacle 203.

(Constitution)
See FIG. In addition to the configuration of the lane state estimation system 100 of the second embodiment shown in FIG. 10, the lane state estimation system 100 of the third embodiment includes an object detection sensor 30, a positioning device 31, and communication mounted on the third vehicle 3. The device 32 and the computer 8 are provided.
The object detection sensor 30 includes a plurality of different types of sensors that detect objects around the third vehicle 3. The positioning device 31 includes a global positioning system (GNSS) receiver, receives radio waves from a plurality of navigation satellites, and measures the current time and the current position and traveling direction of the third vehicle 3.
The object detection sensor 30 and the positioning device 31 may have the same configuration as the object detection sensor 10 and the positioning device 11 of the first vehicle 1, for example.

The communication device 32 distributes the reference time to the object detection sensor 30 based on the current time information obtained from the positioning device 31. Further, the communication device 32 exchanges data with the object detection means 41 via the communication means 40 of the computer 4 by a wired or wireless communication means.
The communication device 12 of the first vehicle 1, the communication device 22 of the second vehicle 2, and the communication device 32 of the third vehicle 3 directly communicate with each other by low-delay communication wireless means, and the first vehicle 1 and the third vehicle The current position information of 3 is transmitted to the in-vehicle device 23 of the second vehicle 2. As the wireless system, for example, the DSRC system specified by IEEE802.11p or the cellular V2X system specified by 3GPP Release 14 or later may be used.

The computer 8 includes a communication means 80, operates as an overtaking lane situational awareness means 81, an overtaking gap measuring means 82, and an overtaking determination means 83, and the second vehicle 2 in the target lane 201 has an obstacle 203 in front of the course. Determine if it is possible to overtake.
The communication means 80 exchanges data with the failure section estimation means 61 via the communication means 60 of the computer 6 by a wired or wireless communication means. Further, the communication means 80 transmits the overtaking availability determination result to the in-vehicle device 23 via the communication device 22 of the second vehicle 2.
The computer 8 may be mounted on any of the first vehicle 1 to the third vehicle 3, a vehicle other than the first vehicle 1 to the third vehicle 3, a mobile edge computer on a mobile phone / self-employed network, and a roadside. It may be implemented on an installed road transportation infrastructure server or a cloud server on the Internet.

The functional configuration of the lane state estimation system 100 of the third embodiment will be described with reference to FIG. The lane state estimation system 100 of the third embodiment has the same functional configuration as the lane state estimation system 100 of the second embodiment, and the same components are designated by the same reference numerals to provide duplicate explanations. Omit.
The lane state estimation system 100 of the third embodiment uses the object detection means 41a and 41b having the same functions as the object detection means 41 of the first embodiment and the second embodiment, respectively, of the first vehicle 1 and the third vehicle 3. Implement in. Further, the lane state estimation system 100 includes an object detection sensor 30 and a positioning device 31 of the third vehicle 3, an overtaking lane situation recognition means 81, an overtaking gap measuring means 82, and an overtaking determination means 83.

The object detection sensor 30 measures the position of an object around the third vehicle 3. For example, in the object detection sensor 30, the laser range finder measures the position of an object around the road of about 150 m in a line-of-sight range of a horizontal angle of 360 degrees around the third vehicle, and outputs a point cloud format detection result. In addition, the visible camera outputs image data of objects around the road.

The positioning device 31 measures the current position of the third vehicle 3 in a common coordinate system (for example, a world coordinate system or a map coordinate system) based on predetermined coordinates. The positioning device 11 of the first vehicle 1 and the positioning device 31 of the third vehicle 3 transmit the current positions of the first vehicle 1 and the third vehicle 3 to the track generating means 25 of the second vehicle 2.
The object detection means 41a and 41b detect the positions, speeds, and moving directions of objects around the first vehicle 1 and the third vehicle 3, respectively, based on the detection results of the object detection sensors 10 and 30.

The overtaking lane situational awareness means 81 detects the intermediate vehicle 220 traveling between the first vehicle 1 and the third vehicle 3 based on the detection results of the object detection means 41a and 41b. The overtaking lane situational awareness means 81 determines whether or not the intermediate vehicle 220 has a function of transmitting its own position like the first vehicle 1 and the third vehicle. For example, it is determined whether or not the intermediate vehicle 220 has a self-position transmission function depending on whether or not the communication means 80 has received the self-position information of the intermediate vehicle 220.

When the intermediate vehicle 220 does not have the function of transmitting the self-position, the overtaking lane situational awareness means 81 is the first between the first vehicle 1 and the intermediate vehicle 220 based on the detection result of the object detection means 41a. 1 Detects the inter-vehicle distance D1. Further, based on the detection result of the object detection means 41b, the second inter-vehicle distance D2 between the third vehicle 3 and the intermediate vehicle 220 is detected.

Further, the overtaking lane situational awareness means 81 calculates the current position of the intermediate vehicle 220 based on the detection result of the object detection means 41a or the object detection means 41b. The overtaking lane situational awareness means 81 transmits the current position of the intermediate vehicle 220 to the track generation means 25 of the two vehicles 2.
Further, the overtaking lane situational awareness means 81 calculates the distance between the first vehicle 1 and the third vehicle 3 based on the current positions of the first vehicle 1 and the third vehicle 3.

Further, the overtaking lane situational awareness means 81 detects the vehicle length L of the intermediate vehicle 220 based on the detection result of the object detection means 41a or 41b.
The overtaking lane situational awareness means 81 may estimate the vehicle length L of the intermediate vehicle 220. For example, the overtaking lane situational awareness means 81 measures the vehicle width of the intermediate vehicle 220 from the detection result of the object detection means 41a or 41b, and estimates the vehicle length that can be assumed from the vehicle width of the intermediate vehicle 220 as the vehicle length L. You can. Further, for example, by performing image recognition processing on the image of the intermediate vehicle 220 by the object detection means 41a or 41b, the vehicle type of the intermediate vehicle 220 may be specified and the vehicle length L may be estimated from the known vehicle specification data. Good.

The overtaking gap measuring means 82 determines whether or not the total of the first inter-vehicle distance D1, the second inter-vehicle distance D2, and the vehicle length L matches the distance between the first vehicle 1 and the third vehicle 3. To do. “Match” means that the difference between the total of the first inter-vehicle distance D1, the second inter-vehicle distance D2 and the vehicle length L and the distance between the first vehicle 1 and the third vehicle 3 is less than a predetermined margin of error. Means. The overtaking gap measuring means 82 outputs the determination result to the overtaking determination means 83.

When the sum of the first inter-vehicle distance D1, the second inter-vehicle distance D2, and the vehicle length L and the distance between the first vehicle 1 and the third vehicle 3 match, the overtaking determination means 83 uses the vehicles 204a to 204c. The distance D3 (overtaking required distance D3) required for the second vehicle 2 behind the target lane 201 in the traveling direction to change lanes to the oncoming lane 202 and overtake the vehicles 204a to 204c and the obstacle 203 is calculated.

Specifically, the overtaking determination means 83 calculates the overtaking required distance D3 according to the following equation.
Overtaking required distance D3 = Speed limit x Overtaking required time + (Inter-vehicle distance + Vehicle length) x Number of vehicles in queue Note that the overtaking required time is the time required to change lanes from the target lane 201 to the oncoming lane 202. Is the total time required to return from the oncoming lane 202 to the target lane 201. Further, in the above formula for calculating the required overtaking distance D3, the average inter-vehicle distance and the average vehicle length when the vehicle is stopped, which are obtained in advance, are used as the inter-vehicle distance and the vehicle length. As described above, the required overtaking distance D3 is the distance D3 required for the second vehicle 2 to change lanes to the oncoming lane 202 and overtake the vehicles 204a to 204c and the obstacle 203, and the calculation formula is the above formula. Not limited.

The overtaking determination means 83 compares the first inter-vehicle distance D1 and the second inter-vehicle distance D2 with the required overtaking distance D3. When the first inter-vehicle distance D1 is longer than the required overtaking distance D3, the overtaking determination means 83 moves the second vehicle 2 into the oncoming lane 202 at the timing when the first vehicle 1 passes by the side of the second vehicle 2. It is determined that the lane can be changed and the obstacle 203 can be overtaken.

Further, when the second inter-vehicle distance D2 is longer than the required overtaking distance D3, the overtaking determination means 83 causes the second vehicle 2 to move to the oncoming lane 202 at the timing when the intermediate vehicle 220 passes by the side of the second vehicle 2. It is determined that the lane can be changed to and the obstacle 203 can be overtaken.
On the contrary, when both the first inter-vehicle distance D1 and the second inter-vehicle distance D2 are equal to or less than the required overtaking distance D3, the overtaking determination means 83 causes the first vehicle 1 to move to the side of the second vehicle 2. It is determined that the second vehicle 2 cannot overtake the obstacle 203 at both the timing of passing and the timing of the intermediate vehicle 220 passing by the side of the second vehicle 2.

If the sum of the first inter-vehicle distance D1, the second inter-vehicle distance D2, and the vehicle length L does not match the distance between the first vehicle 1 and the third vehicle 3, the overtaking determination means 83 uses the first inter-vehicle distance. It is determined that the distance D1 or the second inter-vehicle distance D2 is not accurately measured. In this case, it is prohibited that the second vehicle 2 overtakes the obstacle 203 at the timing when the first vehicle 1 passes the side of the second vehicle 2 and the timing when the intermediate vehicle 220 passes the side of the second vehicle 2. The overtaking determination means 83 outputs the determination result to the trajectory generation means 25.

When it is determined that the obstacle 203 can be overtaken at the timing when the first vehicle 1 passes by the side of the second vehicle 2, the track generating means 25 passes the first vehicle 1 by the side of the second vehicle 2. The target lane 201 is changed to the oncoming lane 202 at the timing, the target traveling track and the speed profile to return to the target lane 201 after passing the obstacle existing section 208 are generated, and are output to the traveling control means 26.
The in-vehicle device 23 of the second vehicle 2 notifies that the vehicle-mounted device 23 of the second vehicle 2 can change lanes to the oncoming lane 202 at the timing when the first vehicle 1 passes by the side of the second vehicle 2 and can overtake the obstacle 203 in front of the course. The voice information and the visual information may be notified to the driver and the occupants of the second vehicle 2.

Further, when it is determined that the obstacle 203 can be overtaken at the timing when the intermediate vehicle 220 passes by the side of the second vehicle 2, the track generating means 25 passes the intermediate vehicle 220 by the side of the second vehicle 2. The target lane 201 is changed to the oncoming lane 202 at the timing, the target traveling track and the speed profile to return to the target lane 201 after passing the obstacle existing section 208 are generated, and are output to the traveling control means 26.
The in-vehicle device 23 of the second vehicle 2 notifies that the intermediate vehicle 220 can change lanes to the oncoming lane 202 at the timing when the intermediate vehicle 220 passes by the side of the second vehicle 2 and overtake the obstacle 203 in front of the course. Information and visual information may be notified to the driver and occupants of the second vehicle 2.

On the other hand, when it is determined that the obstacle 203 cannot be overtaken, or the total of the first inter-vehicle distance D1, the second inter-vehicle distance D2 and the vehicle length L, and the distance between the first vehicle 1 and the third vehicle 3. If does not match, the track generating means 25 generates a target running track and a speed profile that stop before the queue section 206, and outputs the target running track and the speed profile to the running control means 26.
The in-vehicle device 23 of the second vehicle 2 may notify the driver or occupant of the second vehicle 2 of audio information or visual information that informs or prompts the vehicle to stop before the queue section 206.

(motion)
Next, an example of the lane state estimation method of the third embodiment will be described with reference to FIG.
In step S20, the positioning device 11 and the positioning device 31 measure the current positions of the first vehicle 1 and the third vehicle 3.
In step S21, the overtaking lane situational awareness means 81 has a first inter-vehicle distance D1 between the intermediate vehicle 220 and the first vehicle 1 which does not have a function of transmitting its own position, and the intermediate vehicle 220 and the third vehicle 3. The second inter-vehicle distance D2 between them is detected.

In step S22, the overtaking lane situational awareness means 81 detects or calculates the vehicle length L of the intermediate vehicle 220.
In step S23, the overtaking gap measuring means 82 determines whether or not the total of the first inter-vehicle distance D1, the second inter-vehicle distance D2, and the vehicle length L matches the distance between the first vehicle 1 and the third vehicle 3. Is determined. When the total (D1 + D2 + L) does not match the distance between the first vehicle 1 and the third vehicle 3 (step S23: N), the process proceeds to step S24. If they match (step S23: Y), the process proceeds to step S25.

In step S24, the overtaking determination means 83 prohibits the second vehicle 2 from overtaking the obstacle 203 at the timing when the first vehicle 1 or the intermediate vehicle 220 passes by the side of the second vehicle 2. The track generating means 25 generates a target traveling track and a speed profile that stop before the queue section 206. After that, the process ends.
In step S25, the overtaking gap measuring means 82 calculates the overtaking required distance D3.

In step S26, the overtaking gap measuring means 82 determines whether or not the first inter-vehicle distance D1 or the second inter-vehicle distance D2 is longer than the required overtaking distance D3. If neither the first inter-vehicle distance D1 nor the second inter-vehicle distance D2 is longer than the overtaking required distance D3 (step S26: N), the process proceeds to step S24.
In step S24, the overtaking determination means 83 is the second vehicle at both the timing when the first vehicle 1 passes by the side of the second vehicle 2 and the timing when the intermediate vehicle 220 passes by the side of the second vehicle 2. 2 determines that the obstacle 203 cannot be overtaken. The track generating means 25 generates a target traveling track and a speed profile that stop before the queue section 206. After that, the process ends.

On the other hand, when the first inter-vehicle distance D1 is longer than the overtaking required distance D3 (step S26: Y), in step S27, the overtaking determination means 83 passes the first vehicle 1 to the side of the second vehicle 2. At this timing, it is determined that the second vehicle 2 can change lanes to the oncoming lane 202 and overtake the obstacle 203. The track generating means 25 changes lanes from the target lane 201 to the oncoming lane 202 at the timing when the first vehicle 1 passes the side of the second vehicle 2, passes the obstacle existing section 208, and then returns to the target lane 201. Generate orbit and velocity profiles. After that, the process ends.

When the second inter-vehicle distance D2 is longer than the required overtaking distance D3 (step S26: Y), the overtaking determination means 83 is the second at the timing when the intermediate vehicle 220 passes by the side of the second vehicle 2. It is determined that the vehicle 2 can change lanes to the oncoming lane 202 and overtake the obstacle 203. The track generating means 25 changes the lane from the target lane 201 to the oncoming lane 202 at the timing when the intermediate vehicle 220 passes by the side of the second vehicle 2, passes the obstacle existing section 208, and then returns to the target lane 201. And generate a speed profile. After that, the process ends.

(Effect of Third Embodiment)
(1) The overtaking lane situational awareness means 81 detects the vehicle distance in the oncoming lane 202 of the target lane 201. The overtaking gap measuring means 82 determines whether or not the vehicle can pass the obstacle 203 while traveling in the oncoming lane 202 based on the vehicle interval, the length of the vehicle queue, and the speed limit.
As a result, it is possible to determine whether or not the vehicle can pass the obstacle 203 while traveling in the oncoming lane 202 in a situation where a vehicle queue is generated in front of the obstacle 203.

(2) The overtaking lane situational awareness means 81 includes the first inter-vehicle distance between the first oncoming vehicle traveling in the oncoming lane and the third oncoming vehicle and the first oncoming vehicle traveling between the second oncoming vehicles. The second inter-vehicle distance between the third oncoming vehicle and the second oncoming vehicle is measured. The overtaking lane situational awareness means 81 detects or estimates the length of the third oncoming vehicle. The overtaking gap measuring means 82 prohibits overtaking of obstacles when the total of the first inter-vehicle distance, the second inter-vehicle distance and the vehicle length does not match the distance between the first oncoming vehicle and the second oncoming vehicle. To do.
Thereby, when traveling in the oncoming lane 202 and overtaking the obstacle 203, it is possible to determine whether or not the inter-vehicle distance in the oncoming lane 202 can be accurately detected.

100 ... Lane state estimation system, 1 ... 1st vehicle, 2 ... 2nd vehicle, 3 ... 3rd vehicle, 4-8 ... Computer, 10, 20, 30 ... Object detection sensor, 11, 21, 31 ... Positioning device, 12, 22, 32 ... Communication device, 23 ... In-vehicle device, 24 ... Actuator, 25 ... Trajectory generating means, 26 ... Travel control means, 40, 50, 60, 70, 80 ... Communication means, 41, 41a, 41b ... Object Detection means, 51 ... lane section detection means, 52 ... speed determination means, 53 ... travelable section detection means, 61 ... obstacle section estimation means, 71 ... direction indicator detection means, 72 ... navigation system, 73 ... matrix characteristic confirmation means , 81 ... Overtaking lane situation recognition means, 82 ... Overtaking gap measuring means, 83 ... Overtaking determination means

Claims (15)

The position of the object around the vehicle is detected by the object detection sensor mounted on the vehicle.
Based on the detection result of the object detection sensor, a queue section in which a lane is generated in the target lane around the vehicle is detected.
Measure the vehicle speed of the vehicle in the queue section and
Based on the detection result of the object detection sensor, a travelable section in which the vehicle can travel at a first predetermined speed or higher is detected in a front section which is a section ahead of the vehicle row in the traveling direction of the target lane.
When the speed of the vehicle in the queue section is equal to or less than the second predetermined speed lower than the first predetermined speed and the travelable section is detected, there is an obstacle to block at least a part of the target lane. I presume that
A method of estimating lane conditions, which is characterized by the fact that. When the object detection sensor is located on one side of the target lane, the lane boundary line representing the lane boundary on the opposite side of the target lane is continuously extended over a predetermined length or longer. The estimation method according to claim 1, wherein the section detected by the detection sensor is detected as the travelable section. When the object detection sensor is located on one side of the target lane, the target existing on the other side of the target lane is continuously extended by the object detection sensor over a predetermined length or longer. The estimation method according to claim 1 or 2, wherein the detected section is detected as the travelable section. The estimation method according to any one of claims 1 to 3, wherein the section in which the vehicle traveling in the front section is traveling at the first predetermined speed or higher is detected as the travelable section. In the queue section, an obstacle existence section, which is a section where the obstacle is presumed to exist, and a quasi-stationary object existence section, which is a section in which the vehicle travels at a speed equal to or lower than the second predetermined speed, are estimated. The estimation method according to any one of claims 1 to 4, wherein the obstacle existence section is a section sandwiched between the quasi-stationary object existence section and the travelable section. A vehicle in which the direction indicator is lit is detected in the queue section, and it is estimated that there is a boundary between the obstacle existing section and the quasi-stationary object existing section ahead of the vehicle in the traveling direction of the target lane. , The estimation method according to claim 5. The characteristics of the convoy are estimated according to the position of the obstacle existing section or the position of the rear end which is the rear side of both ends of the semi-stationary object existing section with reference to the traveling direction of the target lane.
The estimation method according to claim 5 or 6, wherein it is estimated that the obstacle does not exist according to the characteristics of the vehicle row. The estimation method according to claim 7, wherein when an intersection exists in the obstacle existence section, it is estimated that the obstacle does not exist. When the entrance / exit to the facility along the road exists in the obstacle existence section, the residence time of the object in the obstacle existence section is determined, and when the residence time is longer than a predetermined time, it is estimated that the obstacle does not exist. The estimation method according to claim 7 or 8. It is characterized in that it is estimated that the obstacle does not exist when the end point of the curve exists in the obstacle existence section or the distance between the rear end of the quasi-stationary object existence section and the start point of the curve is equal to or less than the threshold value. The estimation method according to any one of claims 7 to 9. The obstacle occurs when the start point of the downhill slope exists in the obstacle existence section, or the distance between the rear end of the quasi-stationary object existence section and the start point of the uphill slope or the end point of the downhill slope is equal to or less than the threshold value. The estimation method according to any one of claims 7 to 10, wherein the estimation method is presumed to be nonexistent. It is characterized in that it is estimated that the obstacle does not exist when the head of the traffic jam exists in the obstacle existence section or the distance between the rear end of the quasi-stationary object existence section and the end of the traffic jam is equal to or less than the threshold value. The estimation method according to any one of claims 7 to 11. Detecting the distance between vehicles in the oncoming lane of the target lane,
Based on the vehicle spacing, the length of the convoy, and the speed limit, it is determined whether or not the vehicle can travel in the oncoming lane and overtake the obstacle.
The estimation method according to any one of claims 1 to 12, characterized in that. The first inter-vehicle distance between the first oncoming vehicle and the first oncoming vehicle running between the first oncoming vehicle and the second oncoming vehicle traveling in the oncoming lane, and the third oncoming vehicle and the second oncoming vehicle. Measure the second inter-vehicle distance to and from the vehicle,
Detecting or estimating the vehicle length of the third oncoming vehicle,
When the total of the first inter-vehicle distance, the second inter-vehicle distance and the vehicle length does not match the distance between the first oncoming vehicle and the second oncoming vehicle, overtaking of the obstacle is prohibited.
13. The estimation method according to claim 13. An object detection sensor mounted on the vehicle to detect the position of an object around the vehicle,
Based on the detection result of the object detection sensor, a queuing section detecting means for detecting a queuing section in which a vehicle lane is generated in a target lane around the vehicle, and a queuing section detecting means.
A vehicle speed measuring means for measuring the vehicle speed of a vehicle in the queue section, and
Based on the detection result of the object detection sensor, a travelable section for detecting a travelable section in which a vehicle can travel at a first predetermined speed or higher in a front section which is a section ahead of the vehicle row in the traveling direction of the target lane. Detection means and
When the speed of the vehicle in the queue section is equal to or less than the second predetermined speed lower than the first predetermined speed and the travelable section is detected, there is an obstacle to block at least a part of the target lane. And the estimation method to estimate
A lane condition estimation system characterized by being provided.

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