Method and system for vehicle operator assistance improvement

• US 20030187578A1
• Filed: 02/03/2003
• Published: 10/02/2003
• Est. Priority Date: 02/01/2002
• Status: Active Grant

• Current Assignee: Nissan Motor Co., Ltd.
• Original Assignee: Nissan Motor Co., Ltd.
• Inventors: Nishira, Hikaru, Kawabe, Taketoshi
• Granted Patent: US 6,873,911 B2
• Time in Patent Office: Days
• US Class Current: 701/301
• CPC Class Codes: B60R 21/0134 responsive to imminent contact with an obstacle , e.g. using radar systems
• CPC Class Codes: B60T 7/16 operated by remote control, i.e. initiating means not mounted on vehicle
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/9318 Controlling the steering
• CPC Class Codes: G01S 2013/93185 Controlling the brakes
• CPC Class Codes: G01S 2013/9319 Controlling the accelerator
• CPC Class Codes: G01S 2013/932 using own vehicle data, e.g. ground speed, steering wheel direction
• CPC Class Codes: G01S 2013/9324 Alternative operation using ultrasonic waves
• CPC Class Codes: G01S 2013/93271 in the front of the vehicles
• CPC Class Codes: G01S 2013/93272 in the back of the vehicles
• CPC Class Codes: G08G 1/0962 having an indicator mounted inside the vehicle, e.g. giving voice messages
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

A method improves operator assistance of an automobile. On substantially real time basis, data on the automobile and on intervehicle relationship involving the automobile are collected. The data are processed to determine variables for evaluation. The determined variables are evaluated to recommend control input.

Claims

1. A method for improving operator assistance of an automobile, the method comprising:

collecting, on substantially real time basis, data on the automobile and on intervehicle relationship involving the automobile;

processing the data to determine variables for evaluation; and

evaluating the determined variables to recommend control input.

2. The method as claimed in claim 1,

wherein the data processing includes:

predicting future behavior of obstacle vehicle around the automobile in response to a given control input to the automobile; and

wherein the evaluating includes;

correlating the predicted Future behavior with the given control input in determining whether or not the given control unit is to be recommended.

3. The method as claimed in claim 2, further comprising:

generating a control signal in response to the recommended control input.

4. The method as claimed in claim 3, wherein the control signal prompts the operator to applying the recommended control input to the automobile.

5. The method as claimed in claim 4, wherein the control signal is an actuator command.

6. The method as claimed in claim 4, wherein the collected data include data on locations of the obstacle vehicle(s) around the automobile and lane(s) adjacent the automobile.

7. The method as claimed in claim 6, wherein the collected data include data on vehicle speed of the automobile.

8. The method as claimed in claim 2, wherein the predicting obstacle vehicles(s) behavior includes:

detecting location of the obstacle vehicle around the automobile;

detecting lanes adjacent the automobile;

detecting vehicle speed of the automobile;

determining relative position to the obstacle vehicle and vehicle speed of the obstacle vehicle to create a map; and

presenting a predictor equation expressing time dependent variations of the intervehicle relationship in the map.

9. The method as claimed in claim 8, wherein the evaluating includes:

correlating the time dependent variations of the intervehicle relationship in the map with future time dependent variation of the recommenced control input.

10. The method as claimed in claim 8, wherein the map and the predictor equation are used in the evaluating to recommend control input.

11. The method as claimed in claim 1, wherein the data processing includes:

generating a grant request for granting a label on one of the obstacle vehicles around the automobile;

generating an elimination request for eliminating a label from the one obstacle vehicle;

recording relationship between each of the obstacle vehicles and a label;

updating the relationship in response to generation of the grant request and the elimination request;

providing an evaluation function including a weighted sum of a first evaluation term for control input to the automobile, a second evaluation term for state of the automobile, and a third evaluation term for risk applied to the automobile by the labeled obstacle vehicle; and

modifying weighting on the third term upon receiving one of the grant request and elimination request with respect to labeling of the associated obstacle vehicle.

12. The method as claimed in claim 8,

wherein the data collecting includes:

monitoring an environment sensing system of the automobile and a state sensing system of the automobile.

13. The method as claimed in claim 12, wherein the evaluating includes:

computing an evaluation index indicative of the result of evaluation of the future time dependent variation of the intervehicle relationship of the obstacle vehicles with respect to future time dependent variation of any given control input; and

finding control input with the best score of the computed evaluation index at each of future time.

14. The method as claimed in claim 13, wherein the evaluating includes:

providing terminal conditions indicative of a desired future behavior of the automobile;

and wherein

the evaluation index is computed with the restraint defined by the terminal conditions.

15. The method as claimed in claim 13, wherein the predictor equation accounts for interaction between the automobile and the obstacle vehicle.

16. The method as claimed in claim 13, wherein, when the automobile determines lane change intention of one of obstacle vehicles via attitude taken by the obstacle vehicle, the predictor equation for the obstacle vehicle is modified

17. The method as claimed in claim 13, wherein, when the automobile is equipped with a road map based guidance system, the predictor equation is modified in response to information provided by the road map based guidance system.

18. The method as claimed in claim 13, wherein the evaluation index includes a plurality of different evaluation functions.

19. The method as claimed in claim 18, wherein the plurality of different evaluation functions are selectively included by the evaluation index in response to desired maneuver(s) preferred by the operator.

20. The method as claimed in claim 18, wherein, when the automobile is equipped with a road map based guidance system, the plurality of different evaluation functions are selectively included by the evaluation index in response to information provided by the road map based guidance system.

21. The method as claimed in claim 14, wherein, when the automobile is equipped with a road map based guidance system, the terminal conditions are created in response to one of control input by the operator and information provided by the road map based guidance system.

22. The method as claimed in claim 12, wherein the recommended control input is updated, and wherein the recommenced control input before updating is used to predict lane change of one of the obstacle vehicles, and the predicted result of lane change is used to change the form of the predictor equation and the form of the evaluation index.

23. The method as claimed in claim 12, further comprising processing the predictor equation using the recommended control input predicts trajectories of the automobile and the obstacle vehicles.

24. The method as claimed in claim 12, wherein the step of evaluating the determined variables to recommend a control input is repeated on time frame driven basis.

25. The method as claimed in claim 12, wherein the step of evaluating the determined variables to recommend a control input is repeated on event driven basis.

26. The method as claimed in claim 12, wherein the step of evaluating the determined variables to recommend a control input is repeated upon event driven basis including occurrence of error in predicting the trajectories.

27. The method as claimed in claim 11,

wherein the generating a grant request includes:

generating a grant request for granting a label on an incoming obstacle vehicle, which has just come into a label granting field around the automobile;

and wherein the generating an elimination request includes;

eliminating an elimination request for eliminating a label from an outgoing obstacle vehicle, which has just left a label holding filed around the automobile and an elimination request for eliminating a label from an obstacle vehicle, which has just disappeared.

28. The method as claimed in claim 11, wherein the updating the relationship includes:

setting a weighting factor providing the weighting on the third term equal to zero upon receiving a grant request for granting a label on the associated obstacle vehicle; and

subsequently increasing the weighting factor from zero at a rate with time.

29. The method as claimed in claim 28, wherein the rate at which the weighting factor is increased is determined by a time-to-collision (TTC) of the automobile with respect to the obstacle vehicle.

30. The method as claimed in claim 28, wherein the rate at which the weighting factor is increased is determined by a time-to-collision (ETC) of the automobile with respect to the obstacle vehicle after an initial stage of increasing of the weighting factor and before a final stage thereof, and during the initial and final stage, the rate at which the weighting factor is set in the neighborhood of zero.

31. The method as claimed in claim 11, wherein the updating the relationship includes:

reducing, at a gradual rate, a weighting factor providing the weighting on the third term toward zero upon receiving an elimination request for eliminating a label from the associated obstacle vehicle; and

subsequently eliminating the label from the associated obstacle vehicle.

32. The method as claimed in claim 31, wherein, when the associated obstacle vehicle disappears before reduction of the weighting factor to zero, the third term estimated by distance to and relative speed to the associated obstacle vehicle immediately before the disappearance.

33. The method as claimed in claim 31, wherein the rate at which the weighting factor is reduced is determined by a time-to-collision (TTC) of the automobile with respect to the obstacle vehicle.

34. The method as claimed in claim 31, wherein the rate at which the weighting factor is reduced is determined by a time-to-collision (TTC) of the automobile with respect to the obstacle vehicle after an initial stage of reducing of the weighting factor and before a final stage thereof, and during the initial and final stage, the rate at which the weighting factor is set in the neighborhood of zero.

35. The method as claimed in claim 11, wherein the control input includes an operator acceleration/deceleration command.

36. The method as claimed in claim 11, wherein the state of the automobile includes vehicle speed of the automobile.

37. The method as claimed in claim 11, wherein the risk increases as the distance to the labeled obstacle vehicle reduces and the relative speed to the labeled vehicle increases.

38. A system for improving operator assistance of an automobile, the system comprising:

sensing devices for collecting, on substantially real time basis, data on the automobile and on intervehicle relationship involving the automobile;

a component for processing the data to determine variables for evaluation; and

a component for evaluating the determined variables to recommend control input.

39. A method for improving operator assistance of an automobile, the method comprising;

collecting, on substantially real time basis, data on the automobile and on intervehicle relationship involving the automobile;

presenting a behavior predictor equations to each of the automobile and obstacle vehicles forming the intervehicle relationship;

presenting an evaluation index including at least one evaluation function;

determining a solution so as to minimize the evaluation index using the behavior predictor equations; and

recommending the determined solution to as control input.

40. A system for improving operator assistance of an automobile, the system comprising:

means for collecting, on substantially real time basis, data on the automobile and on intervehicle relationship involving the automobile;

means for processing the data to determine variables for evaluation; and

means for evaluating the determined variables to recommend control input.