Computer-implemented system and method for detecting vehicle occupancy

1. A computer-implemented system for determining vehicle occupancy, comprising:

light beam pulses emitted from a lidar system to a vehicle passing by the lidar system;

a scanner to generate scans of an object from the light beam pulses, each scan comprising:

a signal receipt module to receive a signal from each of the beam pulses reflected at a point of reflection along a segment of the passing vehicle;

a time module to measure a time from when each beam pulse was emitted from the lidar system to receipt of the signal;

a distance module to calculate a distance of the signal from the lidar system using the measured time;

a position module to position the points of reflection for that vehicle segment in relation to one another as a scan;

a compiler to compile the scans in a consecutive order according to the vehicle and generating a three-dimensional image of an interior of the vehicle from the consecutive scans; and

an occupancy determination module to determine at least one of a presence and absence of vehicle occupancy based on the three-dimensional image, comprising at least one of:

a volume occupancy module to calculate the occupancy by determining a volume within the three-dimensional image, applying a threshold to the volume, and determining that the occupancy exists when the volume satisfies the threshold; and

a shape occupancy module to calculate the occupancy by determining a shape of an object within the three-dimensional image, comparing the shape with a common list of shapes for occupants, and determining the occupancy based on the comparison.

2. A system according to claim 1 , wherein the lidar system is affixed to at least one of a structure in a stationary position and to one or more of lamp posts, bridges, walls, support posts, and barriers.

3. A system according to claim 1 , wherein the three-dimensional image comprises an outline one or more occupants located within the interior of the vehicle.

4. A system according to claim 1 , further comprising:

an occupancy calculation module to calculate a number of occupants, comprising:

a comparison module to compare the volume with a standard volume of an empty vehicle; and

a volume occupancy module to determine the number of occupants based on the volume comparison.

5. A system according to claim 1 , further comprising:

a violation module to determine whether a traffic violation has occurred based on the occupancy, comprising:

a counting module to count a number of occupants;

a threshold module to apply a threshold number of occupants to the counted number of occupants; and

a violation identification module to identify the traffic violation when the counted number of occupants is below the threshold number of occupants.

6. A system according to claim 5 , further comprising:

a database to access raw data as a verification of the image when the traffic violation is identified.

7. A system according to claim 1 , further comprising:

a vehicle determination module to determine a type of the vehicle based on the three-dimensional image.

8. A system according to claim 1 , further comprising:

an image comparison module to compare the three-dimensional image to a model of vehicle seats;

a seat determination module to determine an outline of seats in the vehicle based on the model; and

an occupancy identification module to determine the presence and absence of occupants, comprising at least one of:

an object identification module to identify an object in the three-dimensional image in addition to the seats and determining the presence of occupants in the vehicle based on the identified object; and

an outline module to identify only the outline of seats in the image and determining the absence of occupants in the vehicle.

9. A system according to claim 1 , further comprising:

a photograph of at least a portion of the vehicle; and

an occupancy identification module to utilize the three-dimensional image to disambiguate images within the photograph as a determination of the occupancy.

10. A computer-implemented method for determining vehicle occupancy, comprising:

applying light beam pulses emitted from a lidar system to a vehicle passing by the lidar system;

generating scans of an object from the light beam pulses, each scan comprising:

receiving a signal from each of the beam pulses reflected at a point of reflection along a segment of the passing vehicle,

measuring a time from when each beam pulse was emitted from the lidar system to receipt of the signal;

calculating a distance of the signal from the lidar system using the measured time; and

positioning the points of reflection for that vehicle segment in relation to one another as a scan;

compiling the scans in a consecutive order according to the vehicle and generating a three-dimensional image of an interior of the vehicle from the consecutive scans; and

determining at least one of a presence and absence of vehicle occupancy based on the three-dimensional image, comprising at least one of:

calculating the occupancy, comprising:

determining a volume within the three-dimensional image;

applying a threshold to the volume; and

determining that the occupancy exists when the volume satisfies the threshold; and

calculating the occupancy, comprising:

determining a shape of an object within the three-dimensional image;

comparing the shape with a common list of shapes for occupants; and

determining the occupancy based on the comparison.

11. A method according to claim 10 , further comprising at least one of:

affixing a lidar system to one or more of lamp posts, bridges, walls, support posts, and barriers; and

affixing the lidar system in a stationary position on a structure, wherein the lidar system emits multiple beams.

12. A method according to claim 10 , wherein the three-dimensional image comprises an outline one or more occupants located within the interior of the vehicle.

13. A method according to claim 10 , further comprising:

calculating a number of occupants, comprising:

comparing the volume with a standard volume of an empty vehicle; and

determining the number of occupants based on the volume comparison.

14. A method according to claim 10 , further comprising:

determining whether a traffic violation has occurred based on the occupancy, comprising:

counting a number of occupants; and

applying a threshold number of occupants to the counted number of occupants; and

identifying the traffic violation when the counted number of occupants is below the threshold number of occupants.

15. A method according to claim 14 , further comprising:

accessing raw data as a verification of the image when the traffic violation is identified.

16. A method according to claim 10 , further comprising:

determining a type of the vehicle based on the three-dimensional image.

17. A method according to claim 10 , further comprising:

comparing the three-dimensional image to a model of vehicle seats;

determining an outline of seats in the vehicle based on the model; and

determining the presence and absence of occupants, comprising at least one of:

identifying an object in the three-dimensional image in addition to the seats and determining the presence of occupants in the vehicle based on the identified object; and

identifying only the outline of seats in the image and determining the absence of occupants in the vehicle.

18. A method according to claim 10 , further comprising:

obtaining a photograph of at least a portion of the vehicle; and

utilizing the three-dimensional image to disambiguate the images within the photograph as a determination of the occupancy.