Driving support device

• US 8,947,218 B2
• Filed: 03/23/2010
• Issued: 02/03/2015
• Est. Priority Date: 10/30/2009
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Inventors: Yoshizawa, Shintaro, Kaji, Hirotaka
• Primary Examiner(s): Wu, Daniel
• Assistant Examiner(s): DARAMOLA, ISRAEL O
• Application Number:
  US13/504,373
• Publication Number:
  US 20120218093A1
• Time in Patent Office: 1,778 Days
• Field of Search: 340/436, 340/903, 701/96, 701/301
• US Class Current: 340/435
• CPC Class Codes: B60R 1/00 Optical viewing arrangements; Real-time viewing arrangements for drivers or passengers using optical image capturing systems, e.g. cameras or video systems specially adapted for use in or on vehicles
• CPC Class Codes: B60R 1/24 in front of the vehicle
• CPC Class Codes: B60R 21/0134 responsive to imminent contact with an obstacle , e.g. using radar systems
• CPC Class Codes: B60R 2300/302 combining image information with GPS information or vehicle data, e.g. vehicle speed, gyro, steering angle data
• CPC Class Codes: B60R 2300/307 virtually distinguishing relevant parts of a scene from the background of the scene
• CPC Class Codes: B60W 2050/143 Alarm means
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2540/20 Direction indicator values
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2552/15 Road slope, i.e. the inclination of a road segment in the longitudinal direction
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/20 Static objects
• CPC Class Codes: B60W 2554/4026 Cycles
• CPC Class Codes: B60W 2554/4029 Pedestrians
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/50 : of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2556/60 : using satellite communication
• CPC Class Codes: B60W 2556/65 : Data transmitted between vehicles
• CPC Class Codes: B60W 30/08 : Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 30/095 : Predicting travel path or likelihood of collision
• CPC Class Codes: B60W 40/04 : Traffic conditions
• CPC Class Codes: B60W 50/16 : Tactile feedback to the driver, e.g. vibration or force feedback to the driver on the steering wheel or the accelerator pedal
• CPC Class Codes: B60Y 2300/18158 : Approaching intersection
• CPC Class Codes: G08G 1/163 : involving continuous checking
• CPC Class Codes: G08G 1/166 : for active traffic, e.g. moving vehicles, pedestrians, bikes

Abstract

An ECU of a driving support device predicts the risk of contact between a host vehicle and obstacles around the host vehicle when the host vehicle travels by a driving action related to at least one normative action candidate, which is a normative driving action candidate of the host vehicle for the surrounding conditions of the host vehicle. Therefore, it is possible to provide the normative action candidates considering the risk of contact between the host vehicle and the obstacles around the host vehicle.

Claims

1. A driving support device comprising:

a risk prediction unit that predicts a risk of contact between a host vehicle and obstacles around the host vehicle when the host vehicle travels by a driving action related to at least one normative action candidate, which is a normative driving action candidate of the host vehicle for surrounding conditions of the host vehicle,

wherein the risk prediction unit calculates an existence probability of the obstacle as a one dimensional integral calculation at a cross point between a predicted path of the host vehicle and a predicted path of the obstacle in a space having the position and speed of the host vehicle and the obstacle on the predicted path as coordinate axes, and

wherein the risk prediction unit predicts the risk of contact between the host vehicle and the obstacle by integrating the existence probability of the obstacle over a time between a time when the head of the host vehicle passes through the cross point and a time when the tail of the host vehicle passes through the cross point.

3. The driving support device according to claim 1,

wherein the risk prediction unit recognizes an obstacle on the basis of obstacle information acquired from the obstacles around the host vehicle and information acquired from a database in which any one of information which is more macroscopically associated with the obstacle information and information which is more microscopically associated with the obstacle information is hierarchically stored, and predicts the risk of contact between the obstacle and the host vehicle.

4. The driving support device according to claim 1,

wherein the risk prediction unit predicts the risk of contact between the obstacle and the host vehicle while predicting a normal path, which is the most general path, and an irregular path different from the normal path for paths of the host vehicle or the obstacle in which the predicted destinations are the same.

5. The driving support device according to claim 1,

wherein the risk prediction unit predicts the risk of contact between the obstacle and the host vehicle while predicting an overt path, which is a directly recognizable path of the obstacle, and a latent path, which is a path of the obstacle that cannot be directly recognized, but is expected to exist, for the predicted path of the obstacle.

6. The driving support device according to claim 1,

wherein the risk prediction unit predicts a short-term risk, which is the risk of contact between the obstacle and the host vehicle after a predetermined time has elapsed from the current time, and a long-term risk, which is the risk of contact between the obstacle and the host vehicle after a time longer than the predetermined time has elapsed, when the host vehicle travels by the driving action related to the normative action candidate.

7. The driving support device according to claim 6,

wherein, if the short-term risk is more than a predetermined threshold value, the risk prediction unit stops the prediction of the long-term risk when the host vehicle travels by the driving action related to the normative action candidate.

2. A driving support device comprising:

a risk prediction unit that predicts a risk of contact between a host vehicle and obstacles around the host vehicle when the host vehicle travels by a driving action related to at least one normative action candidate, which is a normative driving action candidate of the host vehicle for surrounding conditions of the host vehicle; and

a movement efficiency acquiring unit that acquires movement efficiency when the host vehicle travels by the driving action related to the normative action candidate,

wherein the risk prediction unit calculates an existence probability of the obstacle as a one dimensional integral calculation at a cross point between a predicted path of the host vehicle and a predicted path of the obstacle in a space having the position and speed of the host vehicle and the obstacle on the predicted path as coordinate axes, and

wherein the risk prediction unit predicts the risk of contact between the host vehicle and the obstacle by integrating the existence probability of the obstacle over a time between a time when the head of the host vehicle passes through the cross point and a time when the tail of the host vehicle passes through the cross point.