System and method for lane departure warning with ego motion and vision

1. An apparatus, comprising:

at least one camera configured to capture at least one image of a traffic lane in front of a vehicle;

an inertial measurement unit (IMU) configured to detect motion characteristics of the vehicle; and

at least one processor configured to:

obtain a vehicle motion trajectory using the IMU and based on vehicle path prediction parameters, wherein the vehicle path prediction parameters include:

first parameters for predicting a path of the vehicle, the first parameters comprising a first path curvature for predicting the path of the vehicle and a first rate of the first path curvature; and

second parameters for predicting the path of the vehicle, the second parameters comprising a second path curvature for predicting the path of the vehicle and a second rate of the second path curvature,

obtain a vehicle vision trajectory based on the at least one image, wherein the vehicle vision trajectory includes at least one lane boundary for a segment of the traffic lane occupied by the vehicle,

determine distances between one or more points on the vehicle and one or more intersection points of the at least one lane boundary based on the obtained vehicle motion trajectory,

determine at least one time to line crossing (TTLC) based on the determined distances and a speed of the vehicle, and

activate a lane departure warning indicator based on the determined at least one TTLC.

2. The apparatus of claim 1 , wherein, to obtain the vehicle motion trajectory, the at least one processor is further configured to:

predict the path of the vehicle using a combination of the first parameters and the second parameters, wherein the combination is weighted based on the speed of the vehicle.

3. The apparatus of claim 2 , wherein the weighted combination weights the first parameters using a weight α and weights the second parameters using a weight 1−α.

4. The apparatus of claim 3 , wherein:

the weight α is applied to the first parameters for vehicle speeds below a first threshold; and

the weight 1−α is applied to the second parameters for vehicle speeds above a second threshold.

5. The apparatus of claim 4 , wherein:

the first parameters comprise a first path curvature κ L and a first rate κ′ L ;

the second parameters comprise a second path curvature κ H and a second rate κ′ H ;

the first path curvature κ L and the second path curvature κ H are combined according to κ=α·κ L +(1−α)·κ H ; and

the first rate κ′ L and the second rate κ′ H are combined according to κ′=α·κ′ L +(1−α)·κ′ H .

6. The apparatus of claim 1 , wherein:

to determine the at least one TTLC, the at least one processor is further configured to determine a plurality of TTLCs each based on a distance between one of the one or more points on the vehicle and one of the one or more intersection points of the at least one lane boundary; and

to activate the lane departure warning indicator, the at least one processor is further configured to compare a threshold with a combination of the plurality of TTLCs with applied weighting factors.

7. The apparatus of claim 1 , wherein the one or more points on the vehicle include a left corner point, a center point, and a right corner point.

8. A vehicle comprising the apparatus according to claim 1 , the vehicle further comprising:

a motor configured to drive wheels of the vehicle;

a chassis supporting axles on which the wheels are mounted;

a steering control configured to generate a steering command configured to control the wheels when the steering control is activated based on a proximity of an identified closest in path vehicle;

a brake actuator configured to actuate brakes for one or more of the wheels; and

a braking control configured to generate a braking command to control the brake actuator based on activation of the lane departure warning indicator.

9. The vehicle according to claim 8 , wherein the vehicle is an electric vehicle.

10. A method, comprising:

capturing at least one image of a traffic lane in front of a vehicle using at least one camera;

detecting motion characteristics of the vehicle using an inertial measurement unit (IMU);

obtaining a vehicle motion trajectory using the IMU and based on vehicle path prediction parameters, wherein the vehicle path prediction parameters include:

first parameters for predicting a path of the vehicle, the first parameters comprising a first path curvature for predicting the path of the vehicle and a first rate of the first path curvature, and

second parameters for predicting the path of the vehicle, the second parameters comprising a second path curvature for predicting the path of the vehicle and a second rate of the second path curvature,

obtaining a vehicle vision trajectory based on the at least one image, wherein the vehicle vision trajectory includes at least one lane boundary for a segment of the traffic lane occupied by the vehicle;

determining distances between one or more points on the vehicle and one or more intersection points of the at least one lane boundary based on the obtained vehicle motion trajectory;

determining at least one time to line crossing (TTLC) based on the determined distances and a speed of the vehicle; and

activating a lane departure warning indicator based on the determined at least one TTLC.

11. The method of claim 10 , wherein obtaining the vehicle motion trajectory includes:

predicting the path of the vehicle using a combination of the first parameters and the second parameters, wherein the combination is weighted based on the speed of the vehicle.

12. The method of claim 11 , wherein the weighted combination weights the first parameters using a weight a and weights the second parameters using a weight 1−α.

13. The method of claim 12 , wherein:

the weight α is applied to the first parameters for vehicle speeds below a first threshold; and

the weight 1−α is applied to the second parameters for vehicle speeds above a second threshold.

14. The method of claim 13 , wherein:

the first parameters comprise a first path curvature κ L and a first rate κ′ L ;

the second parameters comprise a second path curvature κ H and a second rate κ′ H ;

the first path curvature κ L and the second path curvature κ H are combined according to κ=α·κ L +(1−α)·κ H ; and

the first rate κ′ L and the second rate κ′ H are combined according to κ′=α·κ′ L +(1−α)·κ′ H .

15. The method of claim 10 , wherein:

determining the at least one TTLC includes determining a plurality of TTLCs each based on a distance between one of the one or more points on the vehicle and one of the one or more intersection points of the at least one lane boundary; and

activating the lane departure warning indicator includes comparing a threshold with a combination of the plurality of TTLCs with applied weighting factors.

16. The method of claim 10 , wherein the one or more points on the vehicle include a left corner point, a center point, and a right corner point.

17. The method of claim 10 , further comprising:

driving wheels of the vehicle with a motor;

generating a steering command to control the wheels based on activation of the lane departure warning indicator; and

generating a braking command to control a brake actuator based on activation of the lane departure warning indicator.

18. The method according to claim 17 , wherein the vehicle is an electric vehicle.