Vehicle roll over prevention safety driving system and method
First Claim
1. A vehicle rollover prevention safety driving method, comprising the following steps:
- (A) fetching at least a road image in front of said vehicle;
(B) determining if drive lanes are in a road image, in case the answer is negative, return to step (A), otherwise perform step (C);
(C) calculating by a processor a curvature of said drive lane, inclination angle of the road, and the relative positions of said vehicle on said drive lane based on a lane marking;
(D) calculating a rollover prediction point and a rollover threshold speed based on vehicle dynamic information, said curvature of the drive lane, said inclination angle of the road; and
(E) determining if said vehicle speed is over a rollover threshold speed;
in case the answer if negative, returning to said step (C);
otherwise, issuing a warning to driver to slow down said vehicle relative to said rollover prediction point and said rollover threshold speed, wherein in said step (C), a lane marking model is utilized to calculate a slope of said drive lane, said curvature of said drive lane, and said relative positions of said vehicle on said drive lane, wherein the equation of the lane marking model is;
Xw=k·
Yw2+m·
Yw+b, wherein Xw and Yw indicate world coordinate axes, respectively, and k, m, and b are parameters of said lane marking model,wherein the slope El of said drive lane is obtained by applying a first order differentiation to said lane marking model, where El=2·
kYw+m,wherein said curvature Cl of the drive lane is obtained by applying a second order differentiation to said lane marking model, where Cl=2·
k, andwherein said relative positions Δ
Y of said vehicle on said drive lane are obtained as;
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Abstract
A vehicle rollover prevention safety driving system, comprising: at least an image sensor, used to fetch road images in front of said vehicle; an image processor, connected to said image sensor, and is used to identify a drive lane in road images, and calculate a drive lane curvature, an inclination angle of said road, and relative positions of said vehicle and a lane marking; a vehicle conditions sensing module, used to sense dynamic information of a vehicle turning angle, a vehicle inclination angle, and a vehicle speed; a microprocessor, connected to said image processor and said vehicle conditions sensing module, and it calculates a rollover prediction point and a rollover threshold speed, and it issues a corresponding warning signal or a control signal; and an accelerator and brake controller, connected to said microprocessor, and it controls deceleration of said vehicle according to said control signal.
11 Citations
8 Claims
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1. A vehicle rollover prevention safety driving method, comprising the following steps:
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(A) fetching at least a road image in front of said vehicle; (B) determining if drive lanes are in a road image, in case the answer is negative, return to step (A), otherwise perform step (C); (C) calculating by a processor a curvature of said drive lane, inclination angle of the road, and the relative positions of said vehicle on said drive lane based on a lane marking; (D) calculating a rollover prediction point and a rollover threshold speed based on vehicle dynamic information, said curvature of the drive lane, said inclination angle of the road; and (E) determining if said vehicle speed is over a rollover threshold speed;
in case the answer if negative, returning to said step (C);
otherwise, issuing a warning to driver to slow down said vehicle relative to said rollover prediction point and said rollover threshold speed, wherein in said step (C), a lane marking model is utilized to calculate a slope of said drive lane, said curvature of said drive lane, and said relative positions of said vehicle on said drive lane, wherein the equation of the lane marking model is;
Xw=k·
Yw2+m·
Yw+b,wherein Xw and Yw indicate world coordinate axes, respectively, and k, m, and b are parameters of said lane marking model, wherein the slope El of said drive lane is obtained by applying a first order differentiation to said lane marking model, where El=2·
kYw+m,wherein said curvature Cl of the drive lane is obtained by applying a second order differentiation to said lane marking model, where Cl=2·
k, andwherein said relative positions Δ
Y of said vehicle on said drive lane are obtained as; - View Dependent Claims (2, 3, 4, 5)
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6. A vehicle rollover prevention safety driving system, comprising:
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at least an image sensor, said image sensor being adapted to fetch road images in front of said vehicle; an image processor connected to said image sensor, said image processor being adapted to identify a drive lane in road images, and calculate a drive lane curvature, an inclination angle of said road, and relative positions n of said vehicle and a lane marking based on said lane marking model; a vehicle conditions sensing module sensing dynamic information of a vehicle turning angle, a vehicle inclination angle, and a vehicle speed; a microprocessor, connected to said image processor and said vehicle conditions sensing module, and calculating a rollover prediction point and a rollover threshold speed based on a curvature of the road, said inclination angle of said road, and said dynamic information, wherein said microprocessor issues a corresponding warning signal or a control signal; and an accelerator and brake controller connected to said microprocessor, said accelerator and brake controller controlling deceleration of said vehicle according to said control signal, wherein said image processor utilizes a lane marking model to calculate a slope of said drive lane, said drive lane curvature, and relative positions of said vehicle on said drive lane, wherein the equation of the lane marking model is;
Xw=k·
Yw2+m·
Yw+b,wherein Xw and Yw indicate world coordinate axes, respectively, and k, m, and b are parameters of said lane marking model, wherein the slope El of said drive lane is obtained by applying a first order differentiation to said lane marking model, where El=2·
kYw+m,wherein said curvature Cl of the drive lane is obtained by applying a second order differentiation to said lane marking model, where Cl=2·
k, andwherein said relative positions Δ
Y of said vehicle on said drive lane are obtained as; - View Dependent Claims (7, 8)
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Specification