System and method in the prediction of target vehicle behavior based on image frame and normalization

An apparatus, comprising:

• at least one camera configured to capture a series of image frames for traffic lanes in front of an ego vehicle, wherein each of the series of image frames is captured at a different one of a plurality of times, and wherein the traffic lanes include an ego traffic lane occupied by the ego vehicle and an adjacent traffic lane for traffic traveling in a same direction as traffic within the ego traffic lane;
• and
• a target object detection and tracking controller configured to:
• process each of the image frames to detect a target vehicle in the adjacent traffic lane within the respective image frame at a time corresponding to capture of the respective image frame,
• determine, using pixel measurements extracted from the image frames, a predicted time to line crossing for the detected target vehicle to cross into the ego traffic lane from the adjacent traffic lane, and
• control the ego vehicle based on the predicted time to line crossing by the target vehicle into the ego traffic lane from the adjacent traffic lane.

An apparatus, comprising:

• at least one camera configured to capture a series of image frames for traffic lanes in front of an ego vehicle, wherein each of the series of image frames is captured at a different one of a plurality of times;
• and
• a target object detection and tracking controller configured to:
• process each of the image frames using pixel measurements extracted from the respective image frame to determine, from the pixel measurements, a predicted time to line crossing for a target vehicle detected in the respective image frame at a time corresponding to capture of the respective image frame, wherein, to process each of the image frames, the target object detection and tracking controller is further configured to
• determine a width in pixels of an ego traffic lane and a lateral offset in pixels of the target vehicle,
• determine a ratio Ln of the lateral offset of the target vehicle Lt the width of the ego traffic lane Le, and
• determine a rate of arrival R(k) of the target vehicle from the ratio Ln(k) at time k and the ratio Ln(k−1) at time k−1, and control the ego vehicle based on the predicted time to line crossing.

A method, comprising:

• capturing a series of image frames for traffic lanes in front of an ego vehicle using at least one camera, wherein each of the series of image frames is captured at a different one of a plurality of times, and wherein the traffic lanes include an ego traffic lane occupied by the ego vehicle and an adjacent traffic lane for traffic traveling in a same direction as traffic within the ego traffic lane;
• processing each of the image frames to detect a target vehicle in the adjacent traffic lane within the respective image frame at a time corresponding to capture of the respective image frame;
• determining, using pixel measurements extracted from the image frames, a predicted time to line crossing for the detected target vehicle to cross into the ego traffic lane from the adjacent traffic lane;
• and
• controlling the ego vehicle based on the predicted time to line crossing by the target vehicle into the ego traffic lane from the adjacent traffic lane.