# US 11,897,385 B2 · Headlamp encapsulated with camera and artificial intelligence processor to adjust illumination

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- Number: US 11,897,385 B2
- Document ID: US11897385B2
- Status: Granted
- Kind: B2
- Application number: 18/159,056
- Filed: 2023-01-24
- Published: 2023-05-25
- Granted: 2024-02-13
- Earliest claimed: 2020-08-20
- Assignees: Pony AI Inc.
- Applicants: Pony AI Inc.
- Inventors: Timofey Uvarov; Kai Chen
- Web page: https://patentgrep.com/patent/US11897385B2

## CPC

- B60Q 1/143: {combined with another condition, e.g. using vehicle recognition from camera images or activation of wipers}
- B60Q 1/0023: {the element being a sensor, e.g. distance sensor, camera}
- B60Q 1/085: {due to special conditions, e.g. adverse weather, type of road, badly illuminated road signs or potential dangers (B60Q1/10, B60Q1/12, B60Q1/1423 take precedence)}
- G06N 5/04: Inference or reasoning models
- G06N 20/00: Machine learning
- H05B 47/125: by using cameras
- B60Q 2300/056: Special anti-blinding beams, e.g. a standard beam is chopped or moved in order not to blind
- B60Q 2300/112: Vehicle speed
- B60Q 2300/116: Vehicle at a stop
- B60Q 2300/32: Road surface or travel path
- B60Q 2300/324: Road inclination, e.g. uphill or downhill
- B60Q 2300/40: Indexing codes relating to other road users or special conditions
- B60Q 2300/45: Special conditions, e.g. pedestrians, road signs or potential dangers
- B60S 1/56: specially adapted for cleaning other parts or devices than front windows or windscreens {(rear-view mirror arrangements mounted on vehicle exterior including cleaning devices B60R1/0602)}
- B60S 1/60: for signalling devices, e.g. reflectors
- Y02B 20/40: Control techniques providing energy savings, e.g. smart controller or presence detection
- B60Q: ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- H05B: ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
- B60S: SERVICING, CLEANING, REPAIRING, SUPPORTING, LIFTING, OR MANOEUVRING OF VEHICLES, NOT OTHERWISE PROVIDED FOR
- Y02B: CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS

## Abstract

Provided herein is a headlamp assembly comprising a housing that encloses: a sensor that acquires data associated with a surrounding environment; a light source that illuminates a field of view comprising a portion of the surrounding environment; and one or more processors that analyze the acquired data and determine a direction, field of view, power, or an intensity of the illumination of the portion based on the analyzed data.

## Claims

### Claim 1

A headlamp assembly comprising a housing that encloses:
a sensor that acquires data associated with a surrounding environment;
a first light source and a second light source that illuminates a portion of the surrounding environment; and
one or more processors that:
analyze the acquired data to determine a density of entities, the entities comprising one or more vehicles, obstacles, or pedestrians in the surrounding environment;
determine a degree to which to synchronize an intensity of the first light source with an intensity of the second light source based on the density of entities, wherein the synchronization of the respective intensities of the first light source and the second light source comprises:
determining a first intensity of the first light source;
determining a second intensity of the second light source;
determining an adjusted first intensity of the first light source based on a difference between the first intensity and the second intensity;
determining a difference between the first intensity and the adjusted first intensity;
based on the density of entities, determining a weight indicative of a factor to adjust the first intensity, wherein the weight is less than one; and
applying the weight to the difference to adjust the first intensity; and
synchronize the respective intensities based on the applied weight to the difference.

### Claim 2 (depends on 1)

The headlamp assembly of claim 1, wherein the determining of the weight comprises determining the weight to be correlated with the density of entities, wherein the weight is determined to decrease if the density of entities decreases and to increase if the density of entities increases.

### Claim 3 (depends on 1)

The headlamp assembly of claim 1, wherein the determining of the weight is based on a relative difference between a first density of entities within a first region illuminated by the first light source and a second density of entities within a second region illuminated by the second light source.

### Claim 4 (depends on 1)

The headlamp assembly of claim 1, wherein the entities comprise one or more traffic signs.

### Claim 5 (depends on 4)

The headlamp assembly of claim 4, wherein the one or more processors:
determine a first initial direction of illumination of the first light source;
determine a second initial direction of illumination of the second light source;
adjust the first initial direction of illumination by a first amount based on the density of entities and one or more types of the entities;
adjust the second initial direction of illumination by a second amount based on the density of entities and one or more types of the entities; and
synchronize the adjusted first initial direction and the adjusted second initial direction.

### Claim 6 (depends on 5)

The headlamp assembly of claim 5, wherein the synchronizing of the adjusted first initial direction and the adjusted second initial direction is based on an average of the first amount and the second amount.

### Claim 7 (depends on 5)

The headlamp assembly of claim 5, wherein the adjusting of the first initial direction of illumination by the first amount is based on respective directions of movement of the entities.

### Claim 8 (depends on 1)

The headlamp assembly of claim 1, wherein the determining of the weight is based on a density of entities travelling in an opposite direction compared to a direction of travel of the vehicle.

### Claim 9 (depends on 1)

The headlamp assembly of claim 1, wherein the one or more processors:
cause a first field of view of the first light source or a second field of view of the second light source to be narrower in response to determining that the vehicle is carrying out a parking function.

### Claim 10 (depends on 1)

The headlamp assembly of claim 1, wherein the headlamp assembly comprises a cleaner and a sensor, and the one or more processors comprise:
an artificial intelligence (AI) processor that:
obtains an image from a sensor;
analyzes the image to determine a concentration of particulates;
predicts parameters of a cleaning operation to be implemented by the cleaner based on the concentration of particulars, wherein the parameters comprise a duration, a cycle, and a spray velocity of the cleaning operation, wherein the AI processor is trained based on previous training examples of concentrations of particulates and parameters.

### Claim 11

A method implemented by a headlamp processor, the method comprising:
by a sensor, acquiring data associated with a surrounding environment;
by a first light source and a second light source, illuminating a portion of the surrounding environment;
by one or more processors:
analyzing the acquired data to determine a density of entities, the entities comprising one or more vehicles, obstacles, or pedestrians in the surrounding environment;
determining a degree to which to synchronize an intensity of the first light source with an intensity of the second light source based on the density of entities, wherein the synchronization of the respective intensities of the first light source and the second light source comprises:
determining a first intensity of the first light source;
determining a second intensity of the second light source;
determining an adjusted first intensity of the first light source based on a difference between the first intensity and the second intensity;
determining a difference between the first intensity and the adjusted first intensity;
based on the density of entities, determining a weight indicative of a factor to adjust the first intensity, wherein the weight is less than one; and
applying the weight to the difference to adjust the first intensity; and
synchronizing the respective intensities based on the applied weight to the difference.

### Claim 12 (depends on 11)

The method of claim 11, wherein the determining of the weight comprises determining the weight to be correlated with the density of entities, wherein the weight is determined to decrease if the density of entities decreases and to increase if the density of entities increases.

### Claim 13 (depends on 11)

The method of claim 11, wherein the determining of the weight is based on a relative difference between a first density of entities within a first region illuminated by the first light source and a second density of entities within a second region illuminated by the second light source.

### Claim 14 (depends on 12)

The method of claim 12, wherein the entities comprise one or more traffic signs.

### Claim 15 (depends on 14)

The method of claim 14, further comprising, by the one or more processors:
determining a first initial direction of illumination of the first light source;
determining a second initial direction of illumination of the second light source;
adjusting the first initial direction of illumination by a first amount based on the density of entities and one or more types of the entities;
adjusting the second initial direction of illumination by a second amount based on the density of entities and one or more types of the entities; and
synchronizing the adjusted first initial direction and the adjusted second initial direction.

### Claim 16 (depends on 15)

The method of claim 15, wherein the synchronizing of the adjusted first initial direction and the adjusted second initial direction is based on an average of the first amount and the second amount.

### Claim 17 (depends on 15)

The method of claim 15, wherein the adjusting of the first initial direction of illumination by the first amount is based on respective directions of movement of the entities.

### Claim 18 (depends on 11)

The method of claim 11, wherein the determining of the weight is based on a density of entities travelling in an opposite direction compared to a direction of travel of the vehicle.

### Claim 19 (depends on 11)

The method of claim 11, further comprising, by the one or more processors:
causing a first field of view of the first light source or a second field of view of the second light source to be narrower in response to determining that the vehicle is carrying out a parking function.

### Claim 20 (depends on 11)

The method of claim 11, further comprising, by an AI processor of the one or more processors:
obtaining an image from a sensor of the headlamp assembly;
analyzing the image to determine a concentration of particulates;
predicting parameters of a cleaning operation to be implemented by a cleaner of the headlamp assembly based on the concentration of particulars, wherein the parameters comprise a duration, a cycle, and a spray velocity of the cleaning operation, wherein the AI processor is trained based on previous training examples of concentrations of particulates and parameters.