Host-centric method for automobile collision avoidance decisions
First Claim
1. A host vehicle having a plurality of sensors that provide coverage over an entire azimuth around said host vehicle, said host vehicle having a processor that cooperates with said plurality of sensors to perform a method of quantifying a collision risk of said host vehicle with remote objects over said entire azimuth, said method comprising the steps of:
- A) collecting and preserving a short-term history of sensor trajectory data, velocity data, acceleration data and range data and azimuth data pertaining to said objects;
B) identifying leading edges of remote objects according to the minima of said range data and said azimuth data from said step A);
C) linking the most recently identified said leading edges from said step B) individually to said leading edges stored in said short-term history to define said trajectory data of said remote objects based on a frame of reference relative to said host vehicle;
D) calculating said velocity data and said acceleration data of said leading edges based on said trajectory data;
E) quantifying collision risk of the host vehicle with said leading edges to establish a risk value; and
F) determining an evasive maneuver for said host vehicle based on a vector sum of high risk leading edge risks and locations if the collision risk is above said predetermined risk value from said step E).
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Abstract
A method of quantifying a host vehicle'"'"'s collision risk with a foreign object includes the steps of collecting and preserving a short-term history of range and azimuth data on the object and identifying leading edges of the foreign object. The leading edges are linked to previous detected leading edges in the short term history storage data to define a trajectory for the object, and to calculate range and azimuth velocities and accelerations of leading edges of the foreign object based on the leading edge trajectory. A collision risk P is then calculated for the foreign object using the range and azimuth velocities and accelerations according to a predetermined formula. If the collision risk P falls below a pre-set value, the methods of the present invention calculate an evasive maneuver for the host vehicle based on a vector sum of high risk leading edge risks and locations.
63 Citations
6 Claims
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1. A host vehicle having a plurality of sensors that provide coverage over an entire azimuth around said host vehicle, said host vehicle having a processor that cooperates with said plurality of sensors to perform a method of quantifying a collision risk of said host vehicle with remote objects over said entire azimuth, said method comprising the steps of:
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A) collecting and preserving a short-term history of sensor trajectory data, velocity data, acceleration data and range data and azimuth data pertaining to said objects; B) identifying leading edges of remote objects according to the minima of said range data and said azimuth data from said step A); C) linking the most recently identified said leading edges from said step B) individually to said leading edges stored in said short-term history to define said trajectory data of said remote objects based on a frame of reference relative to said host vehicle; D) calculating said velocity data and said acceleration data of said leading edges based on said trajectory data; E) quantifying collision risk of the host vehicle with said leading edges to establish a risk value; and F) determining an evasive maneuver for said host vehicle based on a vector sum of high risk leading edge risks and locations if the collision risk is above said predetermined risk value from said step E). - View Dependent Claims (2, 3, 4, 5, 6)
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Specification