Occupant light exposure detection

1. A system, comprising a processor and a memory, the memory storing instructions executable by the processor to:

determine, from an image including a portion of a surface of a human body, a reflected light intensity from the body surface portion;

determine, a skin reflectance of the body surface portion based on a location of the body surface, a light source, and an image sensor location; and

determine, for the body surface portion, an incoming radiance, based on the skin reflectance and the reflected light intensity.

2. The system of claim 1 , wherein the instructions further include instructions to determine the skin reflectance also based on a pose of the body surface portion, the reflected light intensity, a second incoming radiance of the light source, an angle of incidence to the body surface portion, and an angle of reflection from the body surface portion.

3. The system of claim 2 , wherein the light source is a vehicle light source and the instructions further include instructions to store data including the second incoming radiance of the vehicle light source.

4. The system of claim 2 , wherein the instructions further include instructions to determine the second incoming radiance based on the reflected light intensity from a vehicle part and data including reflectance of the vehicle part.

5. The system of claim 1 , wherein the instructions further including instructions to determine a first incoming radiance for a first light wavelength substantially filtered out by a camera sensor based on (i) the incoming radiance for a second light wavelength included in the image, and (ii) data specifying a camera sensitivity to at least the first and second light wavelengths.

6. The system of claim 1 , wherein the instructions further include instructions to determine the incoming radiance of the body surface portion based on a transmittance of a window glass or a weather condition.

7. The system of claim 1 , wherein the body surface portion of the human body is one of a forehead body surface portion, a face-to-cheek body surface portion, a chin body surface portion, a hand, a chest, a thigh, a knee, an arm, and a leg.

8. The system of claim 1 , wherein the instructions further include instructions to input data including a vehicle location, a body surface portion location, a wavelength of the reflected light intensity, and the light source to a machine learning program and to determine a bidirectional reflectance function based on an output of the machine learning program.

9. The system of claim 8 , wherein the machine learning program is a neural network trained based on a specified incoming radiance and received reflected light intensity.

10. The system of claim 8 , wherein the instructions further include instructions to determine the incoming radiance based on the determined bidirectional reflectance function.

11. The system of claim 1 , wherein the instructions further include instructions to determine an incoming radiance of each pixel included in the identified body surface portion, and to determine the incoming radiance of the body surface portion based on an average of the incoming radiances of the pixels.

12. The system of claim 1 , wherein the instructions further include instructions to actuate, based on the determined incoming radiance, a vehicle cooling actuator, a window tinting actuator, a visor, a seat adjustment actuator, an airflow aiming actuator, or a vehicle heating actuator.

13. The system of claim 1 , wherein the determined skin reflectance specifies (i) an average reflectance across a plurality of wavelength ranges, or (ii) a reflectance for a specific wavelength range.

14. A method, comprising:

determining, from an image including a portion of a surface of a human body, a reflected light intensity from the body surface portion;

determining, a skin reflectance of the body surface portion based on a location of the body surface, a light source, and an image sensor location; and

determining, for the body surface portion, an incoming radiance, based on the skin reflectance and the reflected light intensity.

15. The method of claim 14 , further comprising determining the skin reflectance also based on a pose of the body surface portion, the reflected light intensity, a second incoming radiance of the light source, an angle of incidence to the body surface portion, and an angle of reflection from the body surface portion.

16. The method of claim 14 , further comprising determining the second incoming radiance based on the reflected light intensity from a vehicle part and data including reflectance of the vehicle part.

17. The method of claim 14 , further comprising determining a first incoming radiance for a first light wavelength substantially filtered out by a camera sensor based on (i) the incoming radiance for a second light wavelength included in the image, and (ii) data specifying a camera sensitivity to at least the first and second light wavelengths.

18. The method of claim 14 , further comprising determining the incoming radiance of the body surface portion based on a transmittance of a window glass or a weather condition.

19. The method of claim 14 , further comprising inputting data including a vehicle location, a body surface portion location, a wavelength of the reflected light intensity, and the light source to a machine learning program and determining a bidirectional reflectance function based on an output of the machine learning program.

20. The method of claim 14 , further comprising actuating, based on the determined incoming radiance, a vehicle cooling actuator, a window tinting actuator, a visor, a seat adjustment actuator, an airflow aiming actuator, or a vehicle heating actuator.