Driver fault influence vector characterization

1 . An apparatus, comprising:

an interface configured to receive raw images of one or more objects across a timeseries of frames corresponding to a movement event from a perspective of a vehicle of interest (VoI); and

processing circuitry that is configured to:

track a change in intensity or direction information represented in motion vectors (MVs) generated based on the raw images;

generate, based on the change in the intensity or direction information, a weight of an influence vector representing a VoI influence on the movement event by:

determining if the change in intensity or direction information is substantially uniform for the objects across the timeseries of frames;

if the change is substantially uniform, adding a penalty weight to the weight of the influence vector representing the VoI influence on the movement event;

if the change is not substantially uniform, determining if the change is only for an object, of the one or more objects, that is directly in front of the VoI; and

if the change is only for the object that is in front of the VoI, subtracting a reward weight from the weight of the influence vector representing the VoI influence on the movement event; and

transmit the weight of the influence vector and an identity of the movement event to an assessment system that is configured to utilize the weight of the influence vector in an assessment of the VoI.

2 . The apparatus of claim 1 , wherein the processing circuitry is configured to:

determine if the change is only for an object, of the one or more objects, that is directly in front of the VoI; and

if the change is not only for the object that is directly in front of the VoI, add a penalty weight to the weight of the influence vector representing the VoI influence on the movement event.

3 . The apparatus of claim 1 , wherein the assessment system comprises a driver scoring engine, and the processing circuitry is configured to transmit the influence vector to a driver scoring engine to qualify a driver score based on an event associated with the movement event.

4 . The apparatus of claim 1 , wherein the movement event is selected from a group of movement events consisting of: braking, acceleration, and maneuvering of the VoI or of the one or more objects.

5 . The apparatus of claim 1 , wherein if respective positions of the one or more objects is substantially similar across the timeseries of frames, the change in intensity information represented in the MVs is substantially close to zero.

6 . The apparatus of claim 1 , wherein the processing circuitry is configured to:

if there is the change in intensity information represented in the MVs for each of the objects, determine that the movement event is the VoI accelerating or decelerating, and add a penalty weight to the weight of the influence vector representing the VoI influence on the movement event.

7 . The apparatus of claim 1 , wherein the processing circuitry is configured to:

if only an object, of the one or more objects, that is directly in front of the VoI has a change in the intensity information represented in the MVs, and the VoI is traveling at a constant speed, determine that the movement event is the object that is directly in front of the VoI accelerating or decelerating, and subtract a reward weight from the weight of the influence vector representing the VoI influence on the movement event.

8 . The apparatus of claim 1 , wherein the processing circuitry is configured to:

if the one or more objects has a change in intensity information represented in the MVs, and the VoI is traveling at a constant speed, determine that the movement event is a general traffic slowdown, and subtract a reward weight from the weight of the influence vector representing the VoI influence on the movement event.

9 . The apparatus of claim 1 , wherein the processing circuitry is configured to:

if the change in direction information represented in the MVs is substantially completely in a left direction or substantially completely a right direction across the timeseries of frames for the one or more objects, determine that the movement event is unsafe maneuvering by the VoI, and add a penalty weight to the weight of the influence vector representing the VoI influence on the movement event.

10 . The apparatus of claim 1 , wherein the processing circuitry is configured to:

normalize different intensity or direction information represented in MVs from different Vols or road conditions based on factors selected from a group of factors consisting of: camera frame rate, number of frames across which the movement event is formed, and a speed limit for a road segment.

11 . The apparatus of claim 1 , wherein the processing circuitry is configured to test an artificial intelligence vision model of an autonomous vehicle.

12 . A non-transitory computer-readable medium having stored thereon instructions that, when executed by processing circuitry, cause the processing circuitry to:

track a change in intensity or direction information represented in motion vectors (MVs) generated based on raw images of one or more objects across a timeseries of frames of a movement event from a perspective of a vehicle of interest (VoI);

generate, based on the change in the intensity or direction information, a weight of an influence vector representing a VoI influence on the movement event by:

determining if the change in intensity or direction information is substantially uniform for the objects across the timeseries of frames;

if the change is substantially uniform, adding a penalty weight to the weight of the influence vector representing the VoI influence on the movement event;

if the change is not substantially uniform, determining if the change is only for an object, of the one or more objects, that is directly in front of the VoI; and

if the change is only for the object that is in front of the VoI, subtracting a reward weight from the weight of the influence vector representing the VoI influence on the movement event; and

transmit the weight of the influence vector and an identity of the movement event to an assessment system that is configured to utilize the weight of the influence vector in an assessment of the VoI.

13 . The non-transitory computer-readable medium of claim 12 , wherein the instructions further cause the processing circuitry to:

determine if the change is only for an object, of the one or more objects, that is directly in front of the VoI; and

if the change is not only for the object that is directly in front of the VoI, add a penalty weight to the weight of the influence vector representing the VoI influence on the movement event.

14 . The non-transitory computer-readable medium of claim 12 , wherein the assessment system comprises a driver scoring engine, and the instructions further cause the processing circuitry to transmit the influence vector to a driver scoring engine to qualify a driver score based on an event associated with the movement event.

15 . The non-transitory computer-readable medium of claim 12 , wherein the instructions further cause the processing circuitry to:

if the change in direction information represented in the MVs is substantially completely in a left direction or substantially completely a right direction across the timeseries of frames for the one or more objects, determine that the movement event is unsafe maneuvering by the VoI, and add a penalty weight to the weight of the influence vector representing the VoI influence on the movement event.