Traveling-path prediction apparatus and method for vehicles

• US 5,745,870 A
• Filed: 09/13/1995
• Issued: 04/28/1998
• Est. Priority Date: 09/14/1994
• Status: Expired due to Term

• Current Assignee: Mazda Motor Corporation
• Original Assignee: Mazda Motor Corporation
• Inventors: Yamamoto, Yasunori, Doi, Ayumu, Yoshioka, Tohru
• Primary Examiner(s): NGUYEN, TAN QUANG
• Application Number:
  US08/527,635
• Time in Patent Office: 958 Days
• Field of Search: 364/461, 364/460, 364/462, 364/426.044, 340/903, 340/901, 340/902, 340/943, 342/70, 342/454, 367/99, 367/118, 356/3, 356/141.1
• US Class Current: 701/301
• CPC Class Codes: B60W 2552/20 Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/93185 Controlling the brakes
• CPC Class Codes: G01S 2013/932 using own vehicle data, e.g. ground speed, steering wheel direction
• CPC Class Codes: G01S 2013/93271 in the front of the vehicles

Abstract

A vehicle traveling-path prediction apparatus that detects a stationary object in front of the vehicle by utilizing an obstacle detection device instead of a yaw rate sensor, and predicts a traveling path based on the detected stationary object. The apparatus comprises control unit having an obstacle detection device which receives a detection signal from a radar head unit to detect an obstacle in front of the vehicle, stationary object detection device which receives an output signal from the obstacle detection device to detect the obstacle as a stationary object, a first traveling-path prediction device which receives an output signal from the stationary object detection device, and if there is a stationary object in front of the vehicle, calculates a radius of curvature R1 of a first traveling path, based on data indicative of running conditions of the vehicle, a second traveling-path prediction device which calculates a radius of curvature R2 of a second traveling path, based on a velocity V0 and a steering angle θH, and a selection device which receives a detection signal from the radar head unit and if there is no stationary object in front of the vehicle, selects the second traveling path R2 calculated by the second traveling-path prediction device.

Claims

1. A vehicle traveling-path prediction apparatus which detects an obstacle in front of a vehicle and predicts a traveling path of the vehicle based on the detected obstacle, comprising:

obstacle detection means for emitting a radar wave forward from the vehicle and detecting an obstacle existing in front of the vehicle;

stationary-status judgment means for judging whether the obstacle in front of the vehicle is in a stationary status or not, based on the result from detection by said obstacle detection means; and

traveling-path prediction means for predicting a traveling path of the vehicle from data indicative of running conditions of the vehicle with respect to the obstacle, if said stationary-status judgment means judges that the obstacle is in the stationary status.

2. The vehicle traveling-path prediction apparatus according to claim 1, further comprising:

steering-angle detection means for detecting a steering angle of the vehicle; and

velocity detection means for detecting a velocity of the vehicle;

wherein said traveling-path prediction means includes;

first traveling-path prediction means for, if said stationary-status judgment means judges that the obstacle is in stationary status, predicting a first traveling path of the vehicle from data indicative of running conditions of the vehicle with respect to the obstacle; and

second traveling-path prediction means for, if said stationary-status judgment means judges that the obstacle is not in stationary status, predicting a second traveling path of the vehicle based on the steering angle detected by said steering-angle detection means and the velocity detected by said velocity detection means.

3. The vehicle traveling-path prediction apparatus according to claim 2, wherein said first traveling-path prediction means calculates a radius of curvature of the first traveling path from data indicative of running conditions of the vehicle with respect to the obstacle.

4. The vehicle traveling-path prediction apparatus according to claim 2, wherein said second traveling-path prediction means calculates a radius of curvature of the second traveling path based on the steering angle detected by said steering-angle detection means and the velocity detected by said velocity detection means, and calculates a lateral slip angle of the vehicle.

5. The vehicle traveling-path prediction apparatus according to claim 4, wherein said second traveling-path prediction means calculates the direction of the obstacle viewed from the vehicle, based on the lateral slip angle.

6. The vehicle traveling-path prediction apparatus according to claim 2, further comprising selection means for, if said stationary-status judgment means judges that the obstacle is in stationary status, selecting the first traveling path predicted by said first traveling-path prediction means, while if said stationary-status judgment means judges that the obstacle is not in stationary status, selecting the second traveling path predicted by said second traveling-path prediction means.

7. The vehicle traveling-path prediction apparatus according to claim 2, wherein the data indicative of running conditions of the vehicle are distance between the vehicle and the obstacle, a direction of the obstacle viewed from the vehicle, a relative velocity between the vehicle and the obstacle and a velocity of transverse movement.

8. The vehicle traveling-path prediction apparatus according to claim 2, wherein said first traveling-path prediction means calculates the radius of curvature of the first traveling path from data indicative of running conditions of the vehicle with respect to a plurality of objects.

9. A vehicle traveling-path prediction apparatus according to claim 1, further comprising:

obstacle judgment means for judging whether status of the obstacle judged as in the stationary status by said stationary-status judgment means has changed or not, and whether running conditions of the vehicle with respect to the obstacle have changed or not;

wherein said obstacle detection means detects a plurality of obstacles existing in front of the vehicle;

wherein said stationary-status judgment means respectively judges whether the obstacles in front of the vehicle are in stationary status or not, based on the result from detection by said obstacle detection means, and

wherein said traveling-path prediction means judges whether present data indicative of the running conditions of the vehicle with respect to the objects coincides with previous data used in a previous prediction or not, and if they coincide, predicts a radius of curvature of a traveling-path of the vehicle calculated based on the present data, as a first traveling-path.

10. The vehicle traveling-path prediction apparatus according to claim 9, further comprising:

steering-angle detection means for detecting a steering angle of the vehicle; and

velocity detection means for detecting a velocity of the vehicle,

wherein said traveling-path prediction means includes;

first traveling-path prediction means for, if said stationary-status judgment means judges that the obstacles are in stationary status, predicting a first traveling path of the vehicle from data indicative of running conditions of the vehicle with respect to the obstacles; and

second traveling-path prediction means for, if said stationary-status judgment means judges that the obstacles are not in stationary status, predicting a second traveling path of the vehicle based on the steering angle detected by said steering-angle detection means and the velocity detected by said velocity detection means.

11. The vehicle traveling-path prediction apparatus according to claim 10, wherein said first traveling-path prediction means calculates a radius of curvature of the first traveling path from data indicative of running conditions of the vehicle with respect to the respective obstacles.

12. The vehicle traveling-path prediction apparatus according to claim 11, wherein if there are three or more obstacles, said first traveling-path prediction means selects a first obstacle farthest from the vehicle, a second obstacle second farthest from the vehicle and a third obstacle third farthest from the vehicle, and predicts an average value of radius of curvatures of traveling-paths calculated from the data indicative of running conditions of the vehicle with respect to each obstacle, as the first traveling path.

13. The vehicle traveling-path prediction apparatus according to claim 10, wherein said second traveling-path prediction means calculates a radius of curvature of the second traveling path based on the steering angle detected by said steering-angle detection means and the velocity detected by said velocity detection means, and calculates a lateral slip angle of the vehicle.

14. The vehicle traveling-path prediction apparatus according to claim 10, wherein the data indicative of running conditions of the vehicle with respect to the respective obstacles are distances between the vehicle and the obstacles, directions of the obstacles viewed from the vehicle, relative velocities between the vehicle and the obstacles and a velocity of transverse movement.

15. The vehicle traveling-path prediction apparatus according to claim 9, wherein if the data indicative of the running conditions of the vehicle with respect to the objects does not coincide with the previous data, said traveling-path prediction means newly predicts a traveling path of the vehicle.

16. The vehicle traveling-path prediction apparatus according to claim 9, wherein if a plurality of obstacles existing in front of the vehicle are detected by said obstacle detection means, said traveling-path prediction means predicts a traveling path of the vehicle, based on the farthest obstacle from the vehicle.

17. The vehicle traveling-path prediction apparatus according to claim 1, wherein if a plurality of obstacles existing in front of the vehicle are detected by said obstacle detection means, said traveling-path prediction means predicts a traveling path of the vehicle, based on the farthest obstacle from the vehicle.

18. A vehicle traveling-path prediction method for detecting an obstacle in front of a vehicle and predicting a traveling path of the vehicle based on the detected obstacle, comprising:

an obstacle detection step of emitting a radar wave forward from the vehicle and detecting an obstacle existing in front of the vehicle;

a stationary-status judgment step of judging whether the obstacle in front of the vehicle is in stationary status or not, based on the result from detection at said obstacle detection step; and

a traveling-path prediction step of predicting a traveling path of the vehicle from data indicative of running conditions of the vehicle with respect to the obstacle, if the obstacle is in stationary status at said stationary-status judgment step.

19. The vehicle traveling-path prediction method according to claim 18, further comprising:

a steering-angle detection step of detecting a steering angle of the vehicle, and

a velocity detection step of detecting a velocity of the vehicle;

wherein said traveling-path prediction step includes;

a first traveling-path prediction step of, if it is judged at said stationary-status judgment step that the obstacle is in stationary status, predicting a first traveling path of the vehicle from data indicative of running conditions of the vehicle with respect to the obstacle; and

a second traveling-path prediction step of, if it is judged at said stationary-status judgment step that the obstacle is not in stationary status, predicting a second traveling path of the vehicle based on the steering angle detected at said steering-angle detection step and the velocity detected at said velocity detection step.

20. The vehicle traveling-path prediction method according to claim 19, wherein at said first traveling-path prediction step, a radius of curvature of the first traveling path is calculated from data indicative of from data indicative of running conditions of the vehicle with respect to the obstacle.

21. The vehicle traveling-path prediction method according to claim 19, wherein at said second traveling-path prediction step, a radius of curvature of the second traveling path is calculated based on the steering angle detected at said steering-angle detection step and the velocity detected at said velocity detection step, and a lateral slip angle of the vehicle is calculated.

22. The vehicle traveling-path prediction method according to claim 19, wherein the data indicative of running conditions of the vehicle are a distance between the vehicle and the obstacle, a direction of the obstacle viewed from the vehicle, a relative velocity between the vehicle and the obstacle and a velocity of transverse movement.

23. The vehicle traveling-path prediction method according to claim 19, wherein at said first traveling-path prediction step, a radius of curvature of the first traveling path is calculated from data indicative of running conditions of the vehicle with respect to a plurality of obstacles.

24. The vehicle traveling-path prediction method according to claim 23, wherein if there are three or more obstacles, at said first traveling-path prediction step, three obstacles, from the farthest one, are selected, and an average value of radii of curvatures of traveling-paths are calculated from the data indicative of running conditions, as the first traveling path.

25. A vehicle traveling-path prediction method according to claim 18, further comprising:

a obstacle judgment step of judging whether status of the obstacle judged as in the stationary status at said stationary-status judgment step has changed or not, and whether running conditions of the vehicle with respect to the obstacle have changed or not;

wherein at said obstacle detection step, a plurality of obstacles existing in front of the vehicle are detected;

wherein at said stationary-status judgment step, whether the obstacles in front of the vehicle are in stationary status or not is judged respectively, based on the result from detection of said obstacle detection step; and

wherein at said traveling-path prediction step whether present data indicative of the running conditions of the vehicle with respect to the obstacles coincides with previous data used in a previous prediction or not is judged, and if they coincide, a radius of curvature of a traveling path of the vehicle calculated based on the present data is predicted as a first traveling path.

26. The vehicle traveling-path prediction method according to claim 25, further comprising:

a steering-angle detection step of detecting a steering angle of the vehicle; and

a velocity detection step of detecting a velocity of the vehicle;

wherein said traveling-path prediction step includes;

a first traveling-path prediction step of, if the number of objects judged as in the stationary status at said stationary-status judgment step is a predetermined number or greater, predicting the first traveling path of the vehicle from data indicative of running conditions of the vehicle with respect to the objects; and

a second traveling-path prediction step of, if the number of objects judged as in the stationary status at said stationary-status judgment step is less than the predetermined number, predicting the second traveling path based on the steering angle detected at said steering-angle detection step and the velocity detected at said velocity detection step.

27. The vehicle traveling-path prediction method according to claim 26, wherein at said first traveling-path prediction step, a radius of curvature of the first traveling path is calculated from data indicative of running conditions of the vehicle with respect to the respective obstacles.

28. The vehicle traveling-path prediction method according to claim 27, wherein if there are three or more obstacles, a first obstacle farthest from the vehicle, a second obstacle second farthest from the vehicle and a third obstacle third farthest from the vehicle are selected, and an average value of radius of curvatures of traveling-paths calculated from the data indicative of running conditions of the vehicle with respect to each obstacle is predicted as the first traveling path, at said first traveling-path prediction step.

29. The vehicle traveling-path prediction method according to claim 26, wherein at said second traveling-path prediction step, a radius of curvature of the second traveling path is calculated bas ed on the steering angle detected at said steering-angle detection step and the velocity detected at said velocity detection step, and a lateral slip angle of the vehicle is calculated.

30. The vehicle traveling-path prediction method according to claim 26, wherein the data indicative of running conditions of the vehicle with respect to the respective obstacles are distances between the vehicle and the obstacles, directions of the obstacles viewed from the vehicle, relative velocities between the vehicle and the obstacles and a velocity of transverse movement.

31. The vehicle traveling prediction method according to claim 25, wherein if the data indicative of the running conditions of the vehicle with respect to the objects does not coincide with the previous data, a traveling path of the vehicle is newly predicted at said traveling-path prediction step.

32. The vehicle traveling-path prediction method according to claim 25, wherein if a plurality of obstacles existing in front of the vehicle are detected at said obstacle detection step, at said traveling-path prediction step, a traveling path of the vehicle is predicted, based on the farthest obstacle from the vehicle.

33. The vehicle traveling-path prediction method according to claim 18, wherein if a plurality of obstacles existing in front of the vehicle are detected at said obstacle detection step, at said traveling-path prediction step, a traveling path of the vehicle is predicted, based on the farthest obstacle from the vehicle.