Monitoring and scoring passenger attention

Patent metadata

Field	Value
Publication number	US-2025242814-A1
Application number	US-202519177262-A
Country	US
Kind code	A1
Filing date	Apr 11, 2025
Priority date	Aug 13, 2021
Publication date	Jul 31, 2025
Grant date	—

Abstract

Disclosed herein is a passenger monitoring system for monitoring an observed attribute of a passenger in a vehicle. The observed attribute may include a gaze of the passenger, a head track of the passenger, and other observations about the passenger in the vehicle. Based on the observed attribute(s), a field of view of the passenger may be determined. Based on the field of view, a focus point of the passenger may be determined, where the focus point is estimated to be within the field of view. If a sign (e.g., a road sign, a billboard, etc.) is within the field of view of the passenger, record an attention score for the sign based on a duration of time during which the sign is within the field of view and estimated to be the focus point of the passenger.

First claim

1 .- 25 . (canceled)

26 . A system, the system comprising:
at least one processor configured to:
monitor observed attributes of a plurality of passengers, each of the plurality of passengers being in one of a plurality of vehicles associated with a geographic location, the geographic location including a plurality of objects;
record attention scores for the geographic location, each attention score being associated with one of the plurality of objects, and each attention score being based on the observed attributes;
aggregate the attention scores for the geographic location; and
generate attention impact map data for the plurality of objects using the aggregated attention scores.

27 . The system of claim 26 , wherein the observed attributes include one or more of an emotional reaction of one of the plurality of passengers, and wherein the emotional reaction is based on a facial expression, a gesture, a change in facial expression, or a change in gesture of the passenger.

28 . The system of claim 27 , wherein the at least one processor is further configured to classify the emotional reaction as at least one of a plurality of emotion classifications, and wherein the plurality of emotion classifications comprises at least two of happiness, sadness, annoyance, pleasure, displeasure, or indifference.

29 . The system of claim 26 , wherein the attention scores are further based on a determined field of view of the passenger at the geographic location.

30 . The passenger monitoring system of claim 21 , wherein the plurality of objects comprises one or more signs.

31 . The system of claim 30 wherein the attention scores are further based on an expected time required for the passenger to understand a meaning of the one or more signs.

32 . The system of claim 26 , wherein generating the attention impact map data is further based on object information associated with the plurality of objects, and wherein the object information comprises at least one of a position, a pose, a height, a shape, a width, a length, or an orientation of one or more of the plurality of objects.

33 . The system of claim 26 , wherein generating the attention impact map data is further based on focal point information at the geographic location, and wherein the focal point information comprises at least one of point of interest information, traffic control device information, or obstacle information at the geographic location.

34 . The system of claim 33 , wherein generating the attention impact map data is further based on a first probability associated with the focal point information and a second probability associated with one or more of the plurality of objects.

35 . The system of claim 26 , wherein the attention impact map data comprises grid locations within the geographic location, and wherein each of the grid locations is associated with one or more of the plurality of objects.

36 . The system of claim 26 , wherein the attention impact map data is further based on driver distraction information received from other ones of the plurality of vehicles.

37 . The system of claim 26 , wherein the attention impact map data is further based on an expected focus point of the passenger, and wherein the expected focus point is determined based on an expected response of the passenger to a stimulus.

38 . The system of claim 26 , wherein the at least one processor is further configured to analyze the attention impact map data to estimate a market relevance score associated with one or more of the plurality of objects and determine whether the market relevance score exceeds a threshold relevance.

39 . The system of claim 26 , wherein the observed attributes of the passenger comprise at least one of face information associated with a face of the passenger, apparel information associated with an apparel worn by the passenger, object information associated with an object of the passenger, gesture information associated with a gesture of the passenger, or a location of the passenger within the vehicle.

40 . The system of claim 26 , wherein each attention score is based on a total time that one of the plurality of objects is a focus point of one or more of the plurality of passengers.

41 . The system of claim 26 , wherein generating the attention impact map data is further based on traffic data.

42 . The system of claim 26 , wherein the at least one processor is further configured to cause one or more of the plurality of vehicles to implement an action based on the aggregated attention scores.

43 . The system of claim 26 , wherein the at least one processor is further configured to determine a particular location for a new object using the attention impact map data.

44 . A device, the device comprising:
one or more sensors configured to observe attributes of a plurality of passengers in a plurality of vehicles associated with a geographic location, the geographic location including a plurality of objects; and one or more processors configured to:
monitor the observed attributes of the plurality of passengers, each of the plurality of passengers being in one of the plurality of vehicles;
record attention scores for the geographic location, each attention score being associated with one of the plurality of objects, and each attention score being based on the observed attributes;
aggregate the attention scores for the geographic location; and
generate attention impact map data for the plurality of objects using the aggregated attention scores.

45 . The device of claim 44 , wherein the attention scores are further based on a determined field of view of the passenger at the geographic location.

46 . The device of claim 44 , wherein the plurality of objects comprises one or more signs.

47 . The device of claim 44 , wherein the attention scores are further based on an expected time required for the passenger to understand a meaning of the one or more signs.

48 . The device of claim 44 , wherein the attention impact map data is further based on an expected focus point of the passenger, and wherein the expected focus point is determined based on an expected response of the passenger to a stimulus.

49 . A non-transitory computer readable medium comprising instructions executable by at least one processor to perform a method, the method comprising:
monitor observed attributes of a plurality of passengers, each of the plurality of passengers being in one of a plurality of vehicles associated with a geographic location, the geographic location including a plurality of objects; record attention scores for the geographic location, each attention score being associated with one of the plurality of objects, and each attention score being based on the observed attributes; aggregate the attention scores for the geographic location; and generate attention impact map data for the plurality of objects using the aggregated attention scores.

50 . The non-transitory computer readable medium of claim 49 , wherein the attention scores are further based on a determined field of view of the passenger at the geographic location.

51 . The non-transitory computer readable medium of claim 49 , wherein the plurality of objects comprises one or more signs.

52 . The non-transitory computer readable medium of claim 49 , wherein the attention scores are further based on an expected time require

Assignees

• Mobileye Vision Technologies Ltd

Inventors

• Alvarez Ignacio J
• Buerkle Cornelius
• Geissler Florian
• Juliato Marcio
• Oboril Fabian
• Pasch Frederik
• Simoes Gaspar Ivan

Classifications

• G06V20/59

  inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions · CPC title

• B60W2554/4048

  Field of view, e.g. obstructed view or direction of gaze · CPC title

• G08G1/0145

  for active traffic flow control · CPC title

• G08G1/0133

  for classifying traffic situation · CPC title

• B60W2554/4049

  Relationship among other objects, e.g. converging dynamic objects · CPC title