JP2006309445A - Driving-support device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a driving-support device which forecasts paths, on which a vehicle and an obstacle move, based on map data and multiple kinds of information specifying the present condition, such as the present location of a vehicle, a speed of a vehicle, and proceeding direction and so on, to issue a warning to a driver under more adequate condition. <P>SOLUTION: When the driving-support device detectes an obstacle around its own vehicle 2, the driving-support device forecasts a forecasted movement path of the obstacle from the present location on a map of its own vehicle 2 and map data stored in a map DB 41 (S6), and also forecasts a forecasted movement path of its own vehicle 2 from operation information, transmitted from a vehicle ECU 9, such as a steering angle of its own vehicle 2, a direction of its own vehicle, a turn signal and so on, and the map data stored in the map DB 41 (S7). When determined that the paths cross, the driving-support device computes the arrival times of its own vehicle 2 and obstacle at the crossing spot by using a speed range determination table 50 and speed coefficient tables 51-53 (S9 and S10). <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a driving support device that estimates a movement locus of a vehicle and a detected obstacle, respectively, and issues a warning about a collision with the obstacle, and in particular, current data such as map data and the current location of the vehicle, vehicle speed, and traveling direction. The present invention relates to a driving support device capable of warning a driver under a more appropriate situation by estimating a trajectory of a vehicle and an obstacle moving based on a plurality of pieces of information specifying the situation.

In recent years, from the viewpoint of preventing accidents when driving a vehicle, a driving support device that detects obstacles such as people and bicycles located around the vehicle by using a radar or an image of a captured camera and warns the driver. The number of vehicles on board is increasing. At that time, not only the presence or location of the obstacle and its location, but also a warning of the situation in a more appropriate situation (only necessary timing) There is also a warning about predicting movements. For example, in Japanese Patent Laid-Open No. 2002-340583, information indicating the situation of the surroundings of the host vehicle such as the presence or absence of a front obstacle is obtained from a radar device, and the traveling speed of the host vehicle is traveled from onboard sensors. Obtain information indicating the status, and further determine the position and travel road of the host vehicle using the navigation device, and determine the possibility that the travel of the host vehicle will affect the other vehicle based on the prediction of the course of the host vehicle and the other vehicle. In addition, there is described a surrounding vehicle information providing apparatus capable of appropriately displaying the surrounding traffic situation including surrounding vehicles by extracting other vehicles that are likely to be affected and displaying them on the display means.
JP 2002-340583 A (page 3 to page 5, FIGS. 1 to 6)

  However, in the surrounding vehicle information providing device described in Patent Document 1 described above, when the courses of the host vehicle and other vehicles are predicted, the prediction is based on information acquired from the radar device, the on-vehicle sensors, and the navigation device. However, the information about the host vehicle and other vehicles could not be obtained sufficiently, and the course could not be predicted accurately. In particular, for roads where vehicles pass, there is no one that has basically the same shape for each of a myriad of roads nationwide. For example, the course is predicted by various factors such as the number of lanes, road width, and type of intersection. Made it difficult. Therefore, in the conventional surrounding vehicle information providing device, there is a limit to the accuracy of the prediction, and it has not been possible to appropriately warn the driver.

  The present invention has been made to solve the above-described conventional problems, and the vehicle and the obstacle are identified based on the map data and a plurality of information for specifying the current situation such as the current location, the vehicle speed, and the traveling direction of the vehicle. It is an object of the present invention to provide a driving support apparatus that can warn a driver under a more appropriate situation by estimating a moving locus.

  In order to achieve the above object, a driving support apparatus according to claim 1 of the present application is disposed in a vehicle, an imaging unit that images the periphery of the vehicle, and an obstacle detection that detects an obstacle based on an image captured by the imaging unit. A map data storage means, a current location detection means for detecting the current location of the vehicle, a vehicle state detection means for detecting the vehicle speed and the traveling direction of the vehicle, and the map data storage means. Based on the stored map data and detection results of the current location detection means and vehicle state detection means, a vehicle estimated trajectory creation processing means for estimating a vehicle trajectory on which the vehicle moves, and based on the detection results of the obstacle detection means Obstacle calculating means for detecting a change in the position of the obstacle and calculating the moving speed and moving direction of the obstacle; map data stored in the map data storing means; An obstacle estimated trajectory creation processing means for estimating an obstacle trajectory to which the obstacle moves based on a calculation result of the obstacle calculating means, and a warning for giving a warning when the vehicle trajectory and the obstacle trajectory intersect And means.

The driving support device according to claim 2 is the driving support device according to claim 1, wherein when the vehicle trajectory and the obstacle trajectory intersect, the vehicle speed and traveling direction of the vehicle, and the obstacle The warning means includes: arrival time calculation means for calculating the arrival time of the vehicle and the arrival time of the obstacle on the intersection based on the movement speed and movement direction of the vehicle, and the situation around the vehicle, Provides a warning based on the calculation result of the arrival time calculation means.
Here, “the situation around the vehicle” includes, for example, the presence or absence of a traffic light or a stop line, the lighting color of the traffic light, the slope of the road surface, the shape of the road surface, the position or movement of another detected obstacle, and the like.

  A driving support apparatus according to a third aspect of the present invention is the driving support apparatus according to the second aspect, further comprising obstacle identifying means for identifying the type of obstacle detected by the obstacle detecting means, and the arrival time. The calculating means performs calculation based on the type of obstacle specified by the obstacle specifying means.

  According to a fourth aspect of the present invention, in the driving support device according to the third aspect, the arrival time calculating means determines the moving speed of the obstacle based on the identification result of the obstacle identifying means. In addition, the arrival time of the obstacle is calculated based on the determined moving speed.

  The driving support device according to claim 5 is the driving support device according to claim 3 or claim 4, wherein the arrival time calculation means is a speed of the vehicle speed from the vehicle speed detected by the vehicle state detection means. A range is determined, the arrival time range of the vehicle is calculated based on the determined speed range, and a speed range of the moving speed of the obstacle is determined based on the identification result of the obstacle identifying means. The obstacle arrival time range is calculated from a speed range, and the warning means issues a warning when the vehicle arrival time range and the obstacle arrival time range overlap.

  The driving support device according to claim 6 is the driving support device according to any one of claims 2 to 4, wherein the warning means includes the arrival time of the vehicle calculated by the arrival time calculation means and the obstacle. A warning is issued when the arrival time is within a predetermined time difference.

  A driving support device according to claim 7 is the driving support device according to any one of claims 2 to 6, further comprising road shape detection means for detecting a shape of a road on which the vehicle travels, The arrival time calculation means calculates the arrival time of the obstacle based on the shape of the road detected by the road shape detection means.

  Furthermore, the driving support apparatus according to claim 8 is the traffic signal state detection means for detecting the state of the traffic light based on the image captured by the imaging means in the driving support apparatus according to any one of claims 2 to 7. The arrival time calculation means calculates the arrival time of the obstacle based on the state of the traffic light detected by the traffic light state detection means.

  In the driving support apparatus according to claim 1 having the above-described configuration, the vehicle speed and traveling direction of the vehicle, the moving direction and moving speed of the obstacle are detected, and the vehicle is based on the map data and the detection result stored in the map data storage means. Since the vehicle trajectory and the obstacle trajectory where the obstacle moves are estimated and a warning is issued, the vehicle and the obstacle move based on a plurality of information specifying the current vehicle and the obstacle and the surrounding situation. The trajectory can be estimated. Therefore, in the relationship between the vehicle and the obstacle, the driver can be warned only at a necessary timing in consideration of the current situation. In addition, when an obstacle is located around the vehicle, it is possible to accurately issue a warning notifying the danger, and the vehicle can be driven safely.

  In the driving support device according to claim 2, when the vehicle trajectory and the obstacle trajectory intersect, the vehicle speed and traveling direction of the vehicle, the moving speed and moving direction of the obstacle, and the situation around the vehicle Since the arrival time of the vehicle and the arrival time of the obstacle to the intersecting point are calculated based on the information on the contact of the vehicle and the obstacle based on a plurality of information specifying the current vehicle and the obstacle and the surrounding situation It is possible to estimate the possibility. Therefore, in the relationship between the vehicle and the obstacle, the driver can be warned at a necessary timing in consideration of the current situation.

  In the driving support device according to the third aspect, since the type of obstacle is specified and the arrival time is calculated based on the specified type of obstacle, the type of obstacle (for example, a child pedestrian, an adult The possibility of contact between the vehicle and the obstacle can be estimated more accurately. Therefore, in the relationship between the vehicle and the obstacle, the driver can be warned at a necessary timing in consideration of the current situation.

  In the driving support device according to claim 4, since the type of obstacle is specified, the moving speed is determined based on the specified type of obstacle, and the arrival time is calculated, the type of obstacle (for example, Based on the child pedestrian, adult pedestrian, bicycle, etc.), the possibility of contact between the vehicle and the obstacle can be estimated more accurately. Therefore, in the relationship between the vehicle and the obstacle, the driver can be warned at a necessary timing in consideration of the current situation.

  In the driving support device according to the fifth aspect, the speed range is set with respect to the vehicle speed of the vehicle and the moving speed of the obstacle, the arrival time range is calculated from the set moving range, and a warning is given when the arrival time ranges overlap. Therefore, even when an error occurs between the estimated trajectory and speed of the vehicle and the obstacle and the actual trajectory and speed, it is possible to give an accurate warning in consideration of the error.

  In the driving support device according to the sixth aspect, since the warning is given when the arrival time of the vehicle calculated by the arrival time calculating means and the arrival time of the obstacle are within a predetermined time difference, The driver is notified in advance that there is a possibility of contact, and the driver can then perform appropriate driving operations.

  In the driving support device according to the seventh aspect, the shape of the road on which the vehicle travels is detected and the arrival time is calculated based on the detected shape of the road. For example, the presence or absence of traffic lights and stop lines and the road surface It is possible to more accurately estimate the possibility of contact between the vehicle and the obstacle based on the situation such as the state. Therefore, in the relationship between the vehicle and the obstacle, the driver can be warned at a necessary timing in consideration of the current situation.

  Further, in the driving support device according to the eighth aspect, the state of the traffic light is detected based on the image captured by the imaging means, and the arrival time is calculated based on the detected state of the traffic light. Based on this, it is possible to more accurately estimate the possibility of contact between the vehicle and the obstacle. Therefore, in the relationship between the vehicle and the obstacle, the driver can be warned at a necessary timing in consideration of the current situation.

DESCRIPTION OF EMBODIMENTS Hereinafter, an embodiment of a driving support device according to the present invention will be described in detail with reference to the drawings.
First, a schematic configuration of the driving support device 1 according to the present embodiment will be described with reference to FIG. FIG. 1 is a schematic configuration diagram of a driving support apparatus 1 according to the present embodiment.
As shown in FIG. 1, a driving support apparatus 1 according to this embodiment includes a first camera (imaging unit) 3 and a second camera (imaging unit) 4 installed on a vehicle 2, and a liquid crystal display (warning unit). ) 5, a speaker (warning means) 6, a driving support ECU 7, a current location detection unit 8, a vehicle ECU (vehicle state detection means) 9, and the like.

  The first camera 3 and the second camera 4 use a solid-state imaging device such as a CCD, for example, and are arranged near the upper center of the license plate in front of the vehicle so that the viewing angles of the cameras overlap. A wide range of imaging is possible from the front to the side. The captured image data is analyzed by an obstacle detection processing unit 31 of the driving support ECU 7 as described later, and obstacles (people, bicycles, other vehicles, etc.) located around the vehicle 2 are detected.

  The liquid crystal display 5 is provided on the center console or the panel surface of the vehicle 2. For example, an image captured by the first camera 3 and the second camera 4, a map image indicating the position of the vehicle 2 on the map, In this way, a warning screen (see FIG. 14) for warning the driver of the possibility of collision with an obstacle is displayed by visual means. The liquid crystal display 5 may also be used for a navigation device.

  In addition, the speaker 6 outputs a warning sound or a warning sound (see FIGS. 13, 15, and 16) that warns the driver of the possibility of a collision with an obstacle by an auditory means, as will be described later. It can be used when outputting music or voice guidance output by an audio device or navigation device installed in the vehicle 2.

  A driving assistance ECU (Electronic Control Unit) 7 detects obstacles from images taken by the first camera 3 and the second camera 4 and also routes obstacles (predicted course) based on various information such as map data. And the route of the vehicle (predicted course) is estimated in the same manner. As a result, when it is determined that there is a risk of a collision with an obstacle from the arrival time at the intersection, the driver is warned using the liquid crystal display 5 or the speaker 6. Is what you do. The detailed configuration of the driving assistance ECU 7 will be described later.

  The current location detection unit 8 includes, for example, a GPS 41 position detection function such as a navigation device, a geomagnetic sensor 42 that detects the absolute direction of the vehicle 2, and a map DB 43 in which map data is stored (see FIG. 2). ), It is possible to specify the current location and traveling direction of the vehicle 2 on the map.

The vehicle ECU 9 is an electronic control unit of the vehicle 2 that controls operations of an engine, a transmission, a brake, and the like, and various sensors such as a vehicle speed sensor 12, a steering angle sensor 13, and a gyro sensor 14 are connected thereto. . Here, the vehicle speed sensor 12 is composed of an active wheel speed sensor attached to the wheel of the vehicle 2, detects the rotational speed of the wheel, and outputs a speed signal to the vehicle ECU 9. The steering angle sensor 13 is attached to the inside of the steering device, detects the steering angle when the steering wheel is steered, and outputs a steering angle signal to the vehicle ECU 9. Here, the steering angle sensor 13 is configured to detect the rotation amount of the steering column shaft by an optical sensor or the like. Further, the gyro sensor 14 detects the turning angle of the vehicle 2 and outputs a turning angle signal to the vehicle ECU 9. As the gyro sensor 14, for example, a gas rate gyro, a vibration gyro, or the like is used.
As a result, the vehicle ECU 9 detects the current vehicle speed of the vehicle 2 based on the output signal of the vehicle speed sensor 12 and detects the steering angle of the vehicle 2 based on the output signal of the steering angle sensor 13. Further, by integrating the turning angle detected by the gyro sensor 14, the vehicle direction can be detected.

Next, the configuration related to the control system of the driving support apparatus 1 according to the present embodiment will be described with reference to FIG. FIG. 2 is a block diagram schematically showing a control system of the driving support apparatus 1 according to the present embodiment.
In FIG. 2, the control system of the driving assistance device 1 is configured based on the driving assistance ECU 7 and the control means of the vehicle ECU 9, and predetermined peripheral devices are connected to the control means.

The driving support ECU 7 is configured with the CPU 21 as a core, and a ROM 22 and a RAM 23 which are storage means are connected to the CPU 21. The ROM 22 stores a driving support processing program to be described later, various programs necessary for controlling the liquid crystal display 5 and the speaker 6, the speed range determination table 50, the speed coefficient tables 51 to 53, and the like. The RAM 23 is a memory for temporarily storing various data calculated by the CPU 21.
The CPU 21 includes an obstacle detection processing unit 31, an obstacle calculation processing unit 32, an obstacle identification processing unit 33, an obstacle estimation trajectory creation processing unit 34, a vehicle estimation trajectory creation processing unit 35, and an arrival time calculation processing unit 36. A road shape detection processing unit 37, a traffic light state detection processing unit 38, and a collision determination processing unit 39, which display a warning of contact between the vehicle 2 and an obstacle based on information obtained from the vehicle ECU 9 and each peripheral device. 5 and the speaker 6 are controlled.

Here, the obstacle detection processing unit 31 takes in images captured by the first camera 3 and the second camera 4 and performs analysis processing to detect obstacles on the road surface.
The obstacle calculation processing unit 32 accumulates a predetermined number of detection results of the obstacle detection processing unit 31, and based on the accumulated detection results, the detected obstacle moves at which speed and in which direction. Is detected by calculating (moving speed and moving direction of the obstacle).
Further, the obstacle identification processing unit 33 grasps the shape of the obstacle by matching the obstacle detected by the obstacle detection processing unit 31, and identifies the obstacle as “pedestrian (adult)”, It is specified as one of “pedestrian (child)”, “bicycle”, “wheelchair”, “vehicle”, and “others (obstacles determined not to belong to any of the above five)”.
Also, the obstacle estimated trajectory creation processing unit 34 is one of “pedestrian (adult)”, “pedestrian (child)”, “bicycle”, “wheelchair”, and “vehicle” by the obstacle identification processing unit 33. The obstacle movement direction detected by the obstacle calculation processing unit 32, the current position on the map of the vehicle 2 specified by the current location detection unit 8, and the map stored in the map DB 41 The estimated movement trajectory of the obstacle is predicted from the data.
Further, the vehicle estimated trajectory creation processing unit 35 operates information such as the steering angle of the vehicle 2, the vehicle direction, and the turn signal transmitted from the vehicle ECU 9, the current position and the traveling direction of the vehicle 2 specified by the current location detection unit 8. And the estimated movement locus of the vehicle 2 is predicted from the map data stored in the map DB 41.
The arrival time calculation processing unit 36, when the trajectory of the vehicle 2 and the trajectory of the obstacle estimated by the obstacle estimated trajectory creation processing unit 34 and the vehicle estimated trajectory creation processing unit 35 intersect, (Hereinafter referred to as a collision point) is calculated from the map data, and the arrival time of the vehicle 2 and the obstacle to the collision point is described below as a speed range determination table 50 (see FIG. 3) and speed coefficient tables 51-53. (See FIG. 4). In addition, when calculating the arrival time, the driving support device 1 according to the present embodiment considers an error between the estimated trajectory and speed and the actual trajectory and speed, so that the speed has a certain range. Then, a range of arrival times having a width before and after the arrival time to be calculated is calculated.
The road shape detection processing unit 37 detects the shape of the road on which the vehicle 2 travels from the map data stored in the map DB 41 or the images captured by the first camera 3 and the second camera 4. The road shapes detected here include “intersection signal presence”, “stop line presence”, “crosswalk presence”, “priority road presence”, “entrance road presence”, “road surface There are “gradient”, “step difference on the road surface” and the like. The detected result is used for selecting a speed coefficient by the speed coefficient tables 51 to 53 (see FIG. 4) when the arrival time is calculated by the arrival time calculation processing unit 36.
The traffic light state detection processing unit 38 analyzes images captured by the first camera 3 and the second camera 4 and detects the state of a traffic light (including a pedestrian signal) installed at an intersection. The traffic light states detected here include “lights blue”, “lights yellow”, “lights red”, “lights an arrow signal”, “flashes blue (only pedestrian signal)”, and the like. The detected result is used for selecting a speed coefficient by the speed coefficient tables 51 to 53 (see FIG. 4) when the arrival time is calculated by the arrival time calculation processing unit 36.
The collision determination processing unit 39 determines whether the arrival time is within a predetermined time difference from the arrival time of the vehicle 2 and the obstacle calculated by the arrival time calculation processing unit 36, and determines that the arrival time is within the predetermined time difference. In this case, a later-described warning screen is displayed on the liquid crystal display 5 and a later-described warning sound is output to the speaker 6. Note that the driving support device 1 according to the present embodiment calculates the arrival time range having a width before and after the arrival time when calculating the arrival time as described above. It is possible to determine the time difference between the arrival times by determining the length of the overlapping time in the range of the arrival time 2 and the obstacle arrival time.

  The current location detection unit 8 includes a GPS 41 that detects the current position of the vehicle, a geomagnetic sensor 42 that detects the absolute direction of the vehicle 2, and a map DB (map data storage means) 43 that stores map data. Here, the GPS 41 detects the current location of the vehicle on the earth by receiving the radio wave generated by the artificial satellite. The geomagnetic sensor 42 detects the direction of the vehicle by measuring the geomagnetism. The map DB 43 includes a hard disk in which map data is stored and a driver for reading out the map data recorded in the hard disk and writing predetermined data in the hard disk, and a map of a necessary area based on the detection result of the GPS 41. Read data. In the present embodiment, a hard disk is used as the external storage device and storage medium of the map DB 43, but in addition to the hard disk, a magnetic disk such as a flexible disk can be used as the external storage device. Also, a memory card, magnetic tape, magnetic drum, CD, MD, DVD, optical disk, MO, IC card, optical card, etc. can be used as an external storage device.

  Further, a vehicle speed sensor 12, a steering angle sensor 13, and a gyro sensor 14 are connected to the vehicle ECU 9, and based on the speed signal, the steering angle signal, and the turning angle signal transmitted from the sensors 12, 13, and 14, respectively. The current vehicle speed, steering angle, and own vehicle direction of the vehicle 2 are detected. And the said detection result is transmitted to driving assistance ECU7, and is used for calculation of the arrival time to the locus | trajectory of a vehicle 2, an obstruction, or a collision point.

  Next, the speed range determination table 50 stored in the ROM 22 and used when the arrival time calculation processing unit 36 calculates the arrival time of the obstacle at the collision point will be described with reference to FIG. FIG. 3 is a diagram showing a speed range determination table 50 according to the present embodiment. Here, the speed range determination table 50 shown in FIG. 3 is a table for setting the moving speed of the obstacle with a constant speed range based on the type of the obstacle in order to consider an error with the actual trajectory and speed. Based on the set speed range, the range of the arrival time at the collision point is calculated.

As illustrated in FIG. 3, the speed range determination table 50 includes the types of obstacles identified by the obstacle identification processing unit 33 and the corresponding speed ranges.
Specifically, when the obstacle detected by the obstacle detection processing unit 31 is specified by the obstacle detection processing unit 33 as a child pedestrian, the basic speed is set to 3 km / h. On the other hand, the speed range “3 ± 2 km / h” in which the speed range of 2 km / h is set to the front and rear is selected.
If the obstacle detected by the obstacle detection processing unit 31 is specified by the obstacle detection processing unit 33 as an adult pedestrian, the basic speed is set to 4 km / h, and 3 km is used as the basic speed. A speed range “4 ± 3 km / h” in which the width of the speed of / h is set back and forth is selected.
Further, when the obstacle detection processing unit 33 specifies that the obstacle detected by the obstacle detection processing unit 31 is a wheelchair, the basic speed is set to 3 km / h, and 2 km / h for that. A speed range “3 ± 2 km / h” in which the speed range is set to the front and rear is selected.
In addition, when the obstacle detection processing unit 33 specifies that the obstacle detected by the obstacle detection processing unit 31 is a bicycle, the basic speed is set to 10 km / h, which is 8 km / h. A speed range “10 ± 8 km / h” in which the width of the speed is set back and forth is selected.
Further, when the obstacle detection processing unit 33 specifies that the obstacle detected by the obstacle detection processing unit 31 is a vehicle, the basic speed is the moving speed detected by the obstacle calculation processing unit 32. And a speed range in which a width of 20% of the moving speed (for example, 10 km / h when the detected moving speed is 50 km / h) is set before and after, “detected speed ± (detected speed × 0.2) "is selected. As for the speed of the host vehicle 2, the speed range is set by applying “detected speed ± (detected speed × 0.2)” to the vehicle speed detected by the vehicle ECU 9.

  In the speed range determination table 50 according to the present embodiment, when the detected obstacle is specified as a pedestrian, a wheelchair, or a bicycle, a predetermined speed range is applied. In the same manner as when the vehicle is identified as a vehicle, the basic speed is set as the movement speed detected by the obstacle calculation processing unit 32, and the speed 20% of the movement speed (for example, the detected bicycle is detected). In the case where the moving speed is 10 km / h, a speed range “detection speed ± (detection speed × 0.2)” in which the width of 2 km / h) is set back and forth may be selected.

  Next, the speed coefficient tables 51 to 53 that are stored in the ROM 22 based on FIG. 4 and used when the arrival time calculation processing unit 36 calculates the arrival time of the obstacle to the collision point will be described. FIG. 4 is a diagram showing speed coefficient tables 51 to 53 according to the present embodiment. Here, the speed coefficient tables 51 to 53 shown in FIG. 4 are based on various factors that affect the moving speed of the obstacle detected by the road shape detection processing unit 37, the traffic light state detection processing unit 38, and the like. 3 is a table for selecting a speed coefficient for correcting the speed range selected in the speed range determination table 3 to a more accurate speed range according to the current situation. Then, by multiplying the speed range shown in the speed range determination table 50 of FIG. 3 by the selected speed coefficient, the speed range is corrected to an appropriate range, and the arrival time is calculated.

  As shown in FIG. 4, the speed coefficient tables 51 to 53 include a vehicle speed coefficient table 51 used when the obstacle detected by the obstacle detection processing unit 31 is specified as a vehicle, and an obstacle detection. The pedestrian / wheelchair speed coefficient table 52 used when the obstacle detected by the processing unit 31 is specified as a pedestrian or a wheelchair, and the obstacle detected by the obstacle detection processing unit 31 is a bicycle. It is composed of a bicycle speed coefficient table 53 that is used when it is specified to be present.

  For example, the vehicle speed coefficient table 51 includes a direction of travel based on the estimated trajectory of the host vehicle 2, items that classify elements that affect the moving speed of an obstacle (vehicle), and contents of specific elements. , And corresponding speed coefficients. The pedestrian / wheelchair speed coefficient table 52 is composed of items that classify elements that affect the moving speed of an obstacle (pedestrian or wheelchair), contents of specific elements, and corresponding speed coefficients. Has been. Further, the bicycle speed coefficient table 53 includes items that classify elements that affect the moving speed of an obstacle (bicycle), the contents of specific elements, and the corresponding speed coefficients.

Hereinafter, a specific example of a plurality of patterns will be described with respect to each of the speed coefficient tables 51 to 53. For example, when the trajectory in which the host vehicle 2 travels straight through an intersection is estimated by the vehicle estimation trajectory creation processing unit 35, When the shape of the road on which the obstacle (the opponent vehicle) passes is detected by the road shape detection processing unit 37 that there is no signal and there is a stop line, the speed coefficient “0.2” is selected.
Further, when the trajectory of the host vehicle 2 making a right turn at the intersection is estimated by the vehicle estimated trajectory creation processing unit 35, the state of the traffic signal installed on the road on the side on which the obstacle (partner vehicle) passes is the traffic signal state. When the detection processing unit 38 detects that the light is red, the speed coefficient “0” is selected.
In addition, when the trajectory of the host vehicle 2 that makes a left turn at the intersection is estimated by the vehicle estimation trajectory creation processing unit 35, the oncoming vehicle of the opponent vehicle is further detected as an obstacle by the obstacle identification processing unit 33, and When the trajectory of the oncoming vehicle that makes a right turn at the intersection is estimated by the obstacle estimation trajectory creation processing unit 34, the speed coefficient “0.8” is selected.
In addition, when a pedestrian is detected as an obstacle, and the state of the traffic light installed on the road on the side on which the obstacle (pedestrian) passes is flashing blue by the traffic light state detection processing unit 38 If detected, the speed coefficient “1.2” is selected.
Further, when a bicycle is detected as an obstacle, and the shape of the road on which the obstacle (bicycle) passes is detected as an uphill by the road shape detection processing unit 37, the speed coefficient “0.6” is selected.

  Next, a driving assistance processing program executed by the driving assistance ECU 7 of the driving assistance apparatus 1 according to the present embodiment having the above-described configuration will be described with reference to FIG. FIG. 5 is a flowchart of the driving support processing program in the driving support device 1 according to the present embodiment. The program shown in the flowchart of FIG. 5 below is stored in the ROM 22 or RAM 23 provided in the driving support ECU 7 and is executed by the CPU 21.

  Here, the driving support processing program detects an obstacle located around the host vehicle 2, estimates the movement locus of the detected obstacle and the host vehicle 2, and determines that the locus intersects. In addition, when it is determined that there is a possibility of a collision in consideration of various situations of the host vehicle 2, the obstacle, and the road, a warning process is performed for the driver.

  In the driving support process, first, in step (hereinafter abbreviated as S) 1, the CPU 21 captures images taken by the first camera 3 and the second camera 4, performs an analysis process, and detects an obstacle on the road surface. Judge whether or not. Here, for example, FIG. 6 is a schematic diagram showing the host vehicle 2 and the obstacle when the host vehicle 2 entering the intersection detects an obstacle (bicycle) 61 located on the left sidewalk.

  If it is determined that an obstacle has been detected (S1: YES), the process proceeds to S2, and if it is determined that an obstacle has not been detected (S1: NO), the process waits until it is detected. The

  Next, in S2, by matching the obstacle detected in S1, the shape is grasped, and the obstacle is designated as “pedestrian (adult)”, “pedestrian (child)”, “ It is specified as one of “bicycle”, “wheelchair”, “vehicle”, and “others (obstacles determined not to belong to any of the five)”. In S3, the type of the obstacle specified in S2 is any one of “pedestrian (adult)”, “pedestrian (child)”, “bicycle”, “wheelchair”, and “vehicle”. Is determined.

  As a result, when it is determined that the obstacle is one of “pedestrian (adult)”, “pedestrian (child)”, “bicycle”, “wheelchair”, and “vehicle” (S3: YES) When the process proceeds to S4 and it is determined that the obstacle does not belong to any of the five (S3: NO), the process returns to the determination process of S1 and waits until the obstacle is detected again.

  Subsequently, in S4, the CPU 21 accumulates a predetermined number of obstacle detection results, and based on the accumulated detection results, how fast and in what direction the detected obstacle is moving (movement of the obstacle). (Speed and moving direction) are calculated and detected.

  In S5, it is determined from the obstacle moving speed detected in S4 whether the detected obstacle moving speed is zero, that is, whether the obstacle is stationary. Here, when it is determined that the obstacle is stationary, for example, a parked bicycle or vehicle may be detected as an obstacle.

  As a result of the determination, if it is determined that the detected obstacle is stationary (S5: YES), there is no possibility of colliding with the own vehicle 2, so the process returns to the determination process of S1, and the obstacle is detected again. Wait until it is done. On the other hand, when it is determined that the obstacle is moving in either direction (S5: NO), the process proceeds to S6.

In S6, a future movement trajectory of the detected obstacle (hereinafter referred to as an obstacle trajectory) is first estimated. Here, when the obstacle trajectory is estimated, the current position of the host vehicle 2 is first specified by the coordinates (x0, y0) on the map data by the current position detection unit 8, and the obstacle detected from the relative position. The coordinate position (x1, y1) on the map data is specified. Thereafter, the obstacle locus is estimated using the coordinate position (x1, y1) on the specified map data, the map data, and the moving direction of the obstacle detected in S4.
For example, FIG. 7 and FIG. 8 are schematic diagrams respectively showing the estimated trajectory of the obstacle and the host vehicle 2 at an intersection at a certain time.

Hereinafter, a specific example of the estimation of the obstacle locus will be described with reference to FIGS. 7 and 8.
For example, as shown in FIGS. 7 and 8, if the bicycle 61 detected as an obstacle runs on the sidewalk toward the intersection with the pedestrian crossing (upward in FIG. 7), the specified map data If it is determined from the coordinate position (x1, y1) and the moving direction of the obstacle detected in S4, first, it moves in the direction of the intersection with a distance d between the sidewalk and the road boundary line 62. A first obstacle trajectory 71 is drawn. Thereafter, a second obstacle trajectory 72 is drawn that moves from the coordinates (x2, y2) approaching the pedestrian crossing to a predetermined distance (for example, 2 m) to the coordinates (x3, y3) at the front side corner of the pedestrian crossing. Furthermore, a third obstacle trajectory 73 is drawn which moves from the coordinates (x3, y3) of the front side corner of the pedestrian crossing to the coordinates (x4, y4) of the rear side middle point of the pedestrian crossing.
The above-described obstacle trajectories 71 to 73 make a collision determination with the host vehicle 2 described later.

  Next, in S7, a future movement trajectory of the host vehicle 2 (hereinafter referred to as the host vehicle trajectory) is estimated. Here, when the host vehicle trajectory is estimated, first, the current position detection unit 8 specifies the current position of the host vehicle 2 using coordinates (x0, y0) on the map data. Thereafter, the vehicle trajectory is estimated using the coordinate position (x0, y0) on the specified map data, the map data, the steering angle detected by the vehicle ECU 9, the vehicle direction, the turn signal operation information, and the like.

Below, the specific example of estimation of the own vehicle locus is demonstrated using FIG.7 and FIG.8.
For example, as shown in FIG. 7, when the own vehicle 2 is running on the roadway toward the intersection with the stop line (upward in FIG. 7) and goes straight along the intersection, the coordinate position ( x0, y0) and the information from the vehicle ECU 9, up to the coordinates (x5, y5) of the point where the passage of the intersection is completed with the distance D between the sidewalk and the boundary line 62 of the roadway A straight vehicle trajectory 81 is drawn.
In addition, as shown in FIG. 8, if the own vehicle 2 is running on the roadway toward the intersection with the stop line (upward in FIG. 8), and turns left at the intersection, the coordinate position on the specified map data If it is determined based on (x0, y0) and information from the vehicle ECU 9, the first vehicle that travels straight to the coordinate (x6, y6) first with a distance D between the sidewalk and the road boundary 62. A vehicle trajectory 82 is drawn. Thereafter, a second host vehicle trajectory 83 is drawn that turns to the coordinates (x7, y7) having the same distance D between the sidewalk and the roadway boundary line 62 on the left approach road. Furthermore, a third vehicle trajectory 84 is drawn that goes straight to the coordinates (x8, y8) of the point where the intersection has been completed.
The collision determination with the obstacle mentioned later is made by the above-mentioned own vehicle locus 81 or the own vehicle tracks 82 to 84.

Next, in S8, the CPU 21 determines whether or not the obstacle locus estimated in S6 and S7 intersects with the own vehicle locus. Specifically, it is determined by whether or not there is a coordinate that matches from the coordinate data specifying the obstacle track and the vehicle track.
For example, in FIG. 7, the obstacle trajectories 71 to 73 and the own vehicle trajectory 81 have no matching coordinates and are determined not to intersect. On the other hand, in FIG. 8, the obstacle trajectories 71 to 73 and the own vehicle trajectories 82 to 84 coincide with each other at the coordinates (X, Y) of the point P, and are determined to intersect.

  If it is determined that the obstacle locus and the vehicle locus intersect (S8: YES), the process proceeds to S9, and the coordinates (X, Y) of the intersecting point (collision point) P are calculated from the map data. To do. On the other hand, if it is determined not to intersect (S8: NO), the process returns to the determination process of S1, and waits until an obstacle is detected again.

Subsequently, in S10, the arrival time of the obstacle at the collision point P is detected in the obstacle locus estimated in S6, the coordinates (X, Y) of the collision point P calculated in S9, and in S4. It is calculated using the moving speed of the obstacle, the speed range determination table 50 (see FIG. 3), and the speed coefficient tables 51 to 53 (see FIG. 4).
Furthermore, in S11, the arrival time of the host vehicle 2 at the collision point P is detected by the vehicle ECU 9 and the own vehicle trajectory estimated in S7, the coordinates (X, Y) of the collision point P calculated in S9, and the vehicle ECU 9. It calculates using the vehicle speed of the said own vehicle and the speed range determination table 50 (refer FIG. 3).

Here, FIG. 9 is a diagram showing a calculation formula for the arrival time of the obstacle and the own vehicle at the collision point. Here, when calculating the arrival time, the driving support device 1 according to the present embodiment gives a predetermined range to the speed in order to consider an error between the estimated trajectory and speed and the actual trajectory and speed. Thus, a range of arrival times in which the calculated arrival time has a width before and after is calculated.
Furthermore, regarding the calculation of the arrival time of the obstacle, a more accurate speed range suitable for the current situation is obtained by multiplying the speed range by a speed coefficient considering various factors affecting the speed of the obstacle shown in FIG. Can be obtained.

Specifically, as shown in FIG. 9, the arrival time of the obstacle is calculated from the coordinates (x1, y1) of the obstacle when the obstacle is detected to the coordinates (X, Y) of the collision point P. The trajectory distance is calculated by dividing the speed range selected by the speed range determination table 50 (see FIG. 3) by the value obtained by multiplying the speed coefficient selected by the speed coefficient tables 51-53.
In addition, the arrival time of the host vehicle is calculated by determining the distance of the trajectory from the coordinates (x0, y0) of the host vehicle 2 to the coordinates (X, Y) of the collision point P when the obstacle is detected. It is calculated by dividing by the value of the speed range selected by the table 50 (see FIG. 3).

Below, the specific example of calculation of the arrival time of an obstacle and the own vehicle is demonstrated using FIG.10 and FIG.11.
For example, as shown in FIG. 10, the vehicle 2 is traveling along a roadway toward the intersection where the stop line is located (upward in FIG. 10) and turns left at the intersection. If the CPU 21 detects that the vehicle 61 is traveling on a downhill sidewalk and the pedestrian signal 92 is blinking based on the images captured by the first camera 3 and the second camera 4, the fault As a speed coefficient to be multiplied by the speed range of an object, “1.4” selected when the road surface is a downhill and “1.2” selected when the pedestrian signal is blinking are used.
As a result, when the distance from the coordinate (x1, y1) of the obstacle bicycle 61 to the collision point P is 30 m, the speed range determination table 50 and the bicycle speed coefficient table 53 are used, as shown in FIG. As shown in (1), the arrival time range of 3.6 sec to 32.1 sec is calculated.
On the other hand, when the distance from the coordinates (x0, y0) of the host vehicle 2 to the collision point P is 50 m and the host vehicle 2 is traveling at 22 km / h, as shown in (2) of FIG. A range of arrival time from 6.8 sec to 10.2 sec is calculated.

Further, as shown in FIG. 11, the host vehicle 2 is traveling on the roadway toward the intersection with the stop line (upward direction in FIG. 11) and travels straight on the intersection, which is an obstacle. When the CPU 21 detects that the opponent vehicle 91 turns right after crossing the pedestrian crossing 93 based on the images captured by the first camera 3 and the second camera 4, as a speed coefficient to be multiplied by the speed range of the obstacle, “0.9” selected when there is a pedestrian crossing is used.
As a result, when the distance from the coordinates (x1, y1) of the opponent vehicle 91, which is an obstacle, to the collision point P is 20 m, the speed range determination table 50 and the bicycle speed coefficient table 53 are used, as shown in FIG. As shown in (1), the range of the arrival time of 6.6 sec to 10 sec is calculated.
On the other hand, when the distance from the coordinates (x0, y0) of the host vehicle 2 to the collision point P is 50 m and the host vehicle 2 is traveling at 20 km / h, as shown in (2) of FIG. A range of arrival times from 7.5 sec to 11.2 sec is calculated.

  In S11, it is determined whether or not there is an overlapping period between the range of the arrival time of the obstacle calculated in S9 and S10 and the range of the arrival time of the host vehicle 2. Specifically, when the arrival time range of the obstacle is calculated to be t1 to t2, and the arrival time range of the host vehicle 2 is calculated to be t3 to t4, “t1 ≦ t3 ≦ t2 Or “t1 ≦ t4 ≦ t2” is satisfied, it is determined that there is an overlapping period in the range of the arrival time. Here, FIG. 12 is a schematic diagram showing the range of the arrival time of the obstacle and the range of the arrival time of the host vehicle 2 on the graph along the time axis.

  In FIG. 12, the range of the arrival time of the obstacle and the host vehicle satisfies the relationship of “t1 ≦ t3 ≦ t2”, and the arrival time range includes the upper limit value t2 of the obstacle arrival time range, It is determined that there is an overlapping period of time T, which is a difference in t3, which is the lower limit value of the arrival time range of the host vehicle.

  If it is determined that there is an overlapping period in the range of the arrival time (S11: YES), the process proceeds to S12. If it is determined that there is no overlapping period (S11: NO), the determination process of S1 It returns to and waits until an obstacle is detected again.

  Thereafter, in S12, the driver is warned based on the overlapping period of the obstacle arrival time range calculated in S9 and S10 and the arrival time range of the host vehicle 2, respectively. Here, in the driving support device 1 according to the present embodiment, the warnings that are performed differ depending on the length of the overlap time between the arrival time range of the obstacle and the arrival time range of the host vehicle 2. FIG. 13 is a diagram showing a warning sound pattern output from the speaker 6 according to the overlapping time of arrival times.

As shown in FIG. 13, when the overlap time of the arrival time range of the obstacle and the arrival time range of the host vehicle 2 is 2 seconds or less, in order to notify the driver that it is dangerous, A small warning sound is repeatedly output at a predetermined interval.
In addition, when the overlap time between the arrival time range of the obstacle and the arrival time range of the host vehicle 2 is longer than 2 seconds and not longer than 4 seconds, in order to notify the driver that it is more dangerous, “ A beeping sound that repeats “beep, beep, beep ...” is repeatedly output at predetermined intervals.
In addition, when the overlap time between the arrival time range of the obstacle and the arrival time range of the host vehicle 2 is longer than 4 seconds, “Pi ...” is used to notify the driver of further danger. Will be output continuously.

Furthermore, FIG. 14 is a diagram showing a warning screen displayed on the liquid crystal display 5 according to the overlapping time of arrival times.
As shown in FIG. 14, on the warning screen, a bar graph 95 indicating the overlap time between the arrival time range of the obstacle and the arrival time range of the host vehicle 2 is an image captured by the first camera 3 and the second camera 4. It is additionally displayed in the upper right corner of the normal display screen 96 to be displayed. Here, the bar graph 95 can notify the driver of a specific overlap time depending on the length thereof, and the bar graph 95 is “yellow” when the overlap time is 2 seconds or less and “orange” when the overlap time is 4 seconds or less. If it is longer than 4 seconds, it is displayed in “red”. Accordingly, the driver can easily perceive the danger by viewing the displayed bar graph 95.

As described above in detail, in the driving assistance apparatus 1 according to the present embodiment, when an obstacle located around the host vehicle 2 is detected, the moving direction of the obstacle and the vehicle specified by the current location detection unit 8 are detected. The estimated movement trajectory of the obstacle is predicted from the current position on the map 2 and the map data stored in the map DB 41 (S6), the steering angle of the vehicle 2, the vehicle direction, the blinker, etc. transmitted from the vehicle ECU 9 The estimated movement locus of the host vehicle 2 is predicted from the operation information of the vehicle, the current position of the vehicle 2 specified by the current location detection unit 8, and the map data stored in the map DB 41 (S7), and it is determined that the locus intersects. In this case, the arrival time of the vehicle 2 and the obstacle to the intersecting point is calculated using the speed range determination table 50 (see FIG. 3) and the speed coefficient tables 51 to 53 (see FIG. 4) (S9, S1 Therefore, it is possible to estimate the trajectory that the host vehicle 2 and the obstacle move based on a plurality of pieces of information that specify the current situation such as the current obstacle and the situation of the host vehicle 2 and the shape of the road. Furthermore, the collision time can be calculated more accurately. Accordingly, it is possible to warn the driver about obstacles located in the vicinity only at a more appropriate timing. And a driver | operator can recognize beforehand that there exists a possibility of a contact with an obstruction, and subsequent suitable driving | operation operation | movement is attained.
In addition, regarding the vehicle speed of the vehicle and the moving speed of the obstacle, the speed range is set using the speed range determination table 50 (see FIG. 3) and the arrival time range is calculated from the set moving range. Since the warning is given in the case of overlapping, even if an error occurs between the estimated trajectory and speed of the vehicle 2 and the obstacle and the actual trajectory and speed, an accurate warning in consideration of the error is given. It becomes possible.
For the calculation of the arrival time of the obstacle, a more accurate speed range suitable for the current situation can be obtained by multiplying the speed range by a speed coefficient taking into consideration various factors affecting the speed of the obstacle shown in FIG. Can be obtained.
Furthermore, in the warning, since the type of the warning is changed according to the overlapping time T in the arrival time range, the driver can perform a more appropriate driving operation.

Note that the present invention is not limited to the above-described embodiment, and various improvements and modifications can be made without departing from the scope of the present invention.
For example, in the present embodiment, when a warning is given by the speaker 6, a warning sound is output based on the overlap time between the range of the arrival time of the obstacle and the range of the arrival time of the host vehicle 2. May be performed. For example, as shown in FIG. 15, in order to notify the driver of danger when the overlap time between the arrival time range of the obstacle and the arrival time range of the host vehicle 2 is 2 seconds or less. "Please pay attention" is output.
In addition, when the overlap time between the arrival time range of the obstacle and the arrival time range of the host vehicle 2 is longer than 2 seconds and not longer than 4 seconds, in order to notify the driver that it is more dangerous, “ "This is dangerous."
In addition, if the overlap time between the arrival time range of the obstacle and the arrival time range of the host vehicle 2 is longer than 4 seconds, it is “very dangerous” to inform the driver that it is more dangerous. Audio is output.

Further, in the present embodiment, the warning is performed only when the range of the arrival time of the obstacle and the range of the arrival time of the host vehicle 2 are overlapped. May be performed. For example, as shown in FIG. 16, if the range of the arrival time of the obstacle and the range of the arrival time of the host vehicle 2 do not overlap, “please be careful” to notify the driver that it is dangerous. Is output.
Further, when the range of the arrival time of the obstacle and the range of the arrival time of the host vehicle 2 overlap, a voice “Dangerous” is output in order to notify the driver that it is more dangerous.

  Further, in the present embodiment, a fixed range is given to the arrival time of the obstacle and the host vehicle 2 at the collision point, and a warning is given based on the overlapping time of the arrival time, but the speed range determination table 50 Without using the speed range, a single value is obtained as the arrival time of the obstacle and the own vehicle 2, and a warning is issued when the time difference between the arrival time of the obstacle and the arrival time of the own vehicle 2 is within a certain time. It's also good.

  In the present embodiment, the arrival time of the host vehicle 2 is calculated by giving the current vehicle speed a predetermined range in advance, but the arrival time is calculated by estimating the vehicle speed at the collision point P from the current vehicle speed. May be. Specifically, there is a method in which the vehicle speed of the host vehicle 2 is decelerated from the current vehicle speed to the estimated vehicle speed before reaching the collision point P, and is calculated based on the vehicle speed considering deceleration. For example, if the collision point P is on the pedestrian crossing after turning left at the intersection as shown in FIG. 8, the vehicle speed at the collision point is estimated to be 15 km / h, and the average value of the current vehicle speed and 15 km / h is calculated. Then, it may be used for calculating the arrival time, or it may be used for calculating the arrival time by calculating the vehicle speed to the collision point P by a function (primary function) connecting the current vehicle speed and 15 km / h. .

It is a schematic structure figure of a driving support device concerning this embodiment. It is a block diagram which shows typically the control system of the driving assistance device concerning this embodiment. It is the figure which showed the speed range determination table which concerns on this embodiment. It is the figure which showed the speed coefficient table which concerns on this embodiment. It is a flowchart of the driving assistance processing program in the driving assistance device which concerns on this embodiment. It is the schematic diagram which showed the own vehicle and obstacle when the own vehicle which approachs an intersection detects the obstruction (bicycle) located in the left sidewalk. It is the schematic diagram which each showed the estimated locus | trajectory of the obstruction and the own vehicle in an intersection when a locus | trajectory does not cross | intersect. It is the schematic diagram which each showed the estimated locus | trajectory of the obstruction and the own vehicle in an intersection in case a locus | trajectory crosses. It is the figure which showed the calculation formula of the arrival time to the collision point of an obstruction and the own vehicle. It is the figure which showed the specific example (pattern 1) of calculation of the arrival time to the collision point of an obstruction and the own vehicle. It is the figure which showed the specific example (pattern 2) of calculation of the arrival time to the collision point of an obstruction and the own vehicle. It is the schematic diagram which showed the range of the arrival time of an obstruction, and the range of the arrival time of the own vehicle on the graph along the time axis. It is the figure which showed the pattern of the warning sound output from a speaker by the overlap time of arrival time. It is the figure which showed the warning screen displayed on a liquid crystal display by the overlap time of arrival time. It is the figure which showed the modification of the pattern of the warning sound output from a speaker by the overlap time of arrival time. It is the figure which showed the modification of the pattern of the warning sound output from a speaker by the overlap time of arrival time.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Driving assistance apparatus 2 Own vehicle 3 1st camera 4 2nd camera 5 Liquid crystal display 6 Speaker 7 Driving assistance ECU
8 Current location detector 9 Vehicle ECU
21 CPU
DESCRIPTION OF SYMBOLS 31 Obstacle detection process part 32 Obstacle calculation process part 33 Obstacle specific process part 34 Obstacle estimation locus | trajectory creation process part 35 Vehicle estimated locus | trajectory creation process part 36 Arrival time calculation process part 37 Road shape detection process part 38 Traffic light state detection process Unit 39 Collision determination processing unit 41 GPS
43 Map DB
71-73 obstacle trajectory 81-84 own vehicle trajectory

Claims (8)

An imaging means disposed in the vehicle for imaging the periphery of the vehicle;
In the driving support device having obstacle detection means for detecting an obstacle based on the image taken by the imaging means,
Map data storage means;
Current location detection means for detecting the current location of the vehicle;
Vehicle state detection means for detecting a vehicle speed and a traveling direction of the vehicle;
Vehicle estimation trajectory creation processing means for estimating a vehicle trajectory on which the vehicle moves based on the map data stored in the map data storage means and the detection results of the current location detection means and the vehicle state detection means;
Obstacle calculating means for detecting a position change of the obstacle based on a detection result of the obstacle detecting means, and calculating a moving speed and a moving direction of the obstacle;
Obstacle estimation trajectory creation processing means for estimating an obstacle trajectory to which the obstacle moves based on the map data stored in the map data storage means and the calculation result of the obstacle calculation means;
A driving support device comprising warning means for giving a warning when the vehicle trajectory and the obstacle trajectory intersect. When the vehicle trajectory and the obstacle trajectory intersect, the vehicle trajectory and the traveling direction of the vehicle, the moving speed and moving direction of the obstacle, and the situation around the vehicle An arrival time calculating means for calculating the arrival time of the vehicle and the arrival time of the obstacle,
The driving support device according to claim 1, wherein the warning unit issues a warning based on a calculation result of the arrival time calculation unit. An obstacle identification means for identifying the type of obstacle detected by the obstacle detection means;
The driving support device according to claim 2, wherein the arrival time calculating unit calculates based on the type of the obstacle specified by the obstacle specifying unit.   The arrival time calculating means determines a moving speed of the obstacle based on a specification result of the obstacle specifying means, and calculates an arrival time of the obstacle based on the determined moving speed. Item 4. The driving support device according to Item 3. The arrival time calculating means includes:
While determining the speed range of the vehicle speed from the vehicle speed of the vehicle detected by the vehicle state detection means, calculating the arrival time range of the vehicle by the determined speed range,
While determining the speed range of the movement speed of the obstacle based on the identification result of the obstacle identification means, calculating the arrival time range of the obstacle according to the determined speed range,
The warning means is
The driving support device according to claim 3 or 4, wherein a warning is issued when the arrival time range of the vehicle and the arrival time range of the obstacle overlap.   5. The warning means performs warning when the arrival time of the vehicle calculated by the arrival time calculation means and the arrival time of the obstacle are within a predetermined time difference. The driving support device according to any one of the above. Road shape detecting means for detecting the shape of the road on which the vehicle travels,
The said arrival time calculation means calculates the arrival time of the said obstacle based on the shape of the road detected by the said road shape detection means, The Claim 2 thru | or 6 characterized by the above-mentioned. Driving assistance device. Having a traffic light state detection means for detecting the state of the traffic light based on the image captured by the imaging means;
The arrival time calculation means calculates the arrival time of the obstacle based on the state of the traffic light detected by the traffic light state detection means. Driving assistance device.

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