# US 11,308,316 B1 · Road side vehicle occupancy detection system

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- Number: US 11,308,316 B1
- Document ID: US11308316B1
- Status: Granted
- Kind: B1
- Application number: 17/465,681
- Filed: 2021-09-02
- Granted: 2022-04-19
- Earliest claimed: 2021-09-02
- Assignees: Invision Ai, Inc.
- Applicants: Invision Ai, Inc.
- Inventors: Karim Ali; Zhijie Wang; Seydi Zorlu; Arash Mohtat; Carlos Becker
- Web page: https://patentgrep.com/patent/US11308316B1

## CPC

- G06V 20/586: {of parking space}
- G06V 40/10: Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06F 3/0604: {Improving or facilitating administration, e.g. storage management}
- G06F 3/0626: {Reducing size or complexity of storage systems}
- G06F 3/0629: {Configuration or reconfiguration of storage systems}
- G06F 3/067: {Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]}
- G06F 9/45558: {Hypervisor-specific management and integration aspects}
- G06F 11/1425: {by reconfiguration of node membership}
- G06F 11/1453: {using de-duplication of the data}
- G06F 11/2094: {Redundant storage or storage space (G06F11/2056 takes precedence)}
- G06F 11/301: {where the computing system is a virtual computing platform, e.g. logically partitioned systems (virtual machines G06F9/45533; logical partitioning of resources G06F9/5077)}
- G06F 11/3476: {Data logging (G06F11/14, G06F11/2205 take precedence)}
- G06F 16/182: Distributed file systems
- G06F 16/2365: {Ensuring data consistency and integrity}
- G06F 18/251: {of input or preprocessed data}
- G06V 10/25: Determination of region of interest [ROI] or a volume of interest [VOI]
- G06V 10/34: Smoothing or thinning of the pattern; Morphological operations; Skeletonisation
- G06V 10/82: using neural networks
- G06V 20/52: Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V20/69)
- G06V 20/54: of traffic, e.g. cars on the road, trains or boats
- G06V 20/59: inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V 20/593: {Recognising seat occupancy}
- G06V 40/103: {Static body considered as a whole, e.g. static pedestrian or occupant recognition}
- H04L 67/1046: {Joining mechanisms}
- H04L 67/1048: {Departure or maintenance mechanisms}
- H04N 7/181: {for receiving images from a plurality of remote sources}
- H04N 7/188: {Capturing isolated or intermittent images triggered by the occurrence of a predetermined event, e.g. an object reaching a predetermined position (signal generation from motion picture films H04N5/253)}
- H04N 23/56: provided with illuminating means
- H04N 23/66: Remote control of cameras or camera parts, e.g. by remote control devices
- G06F 2009/45579: {I/O management, e.g. providing access to device drivers or storage}
- G06F 2009/45583: {Memory management, e.g. access or allocation}
- G06F 2009/45595: {Network integration; Enabling network access in virtual machine instances}
- G06V 2201/08: Detecting or categorising vehicles
- H04L 67/1097: for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION

## Abstract

A system for detecting occupancy of a vehicle travelling in a direction of travel along a road. The system includes a roadside imaging device positioned on a roadside, and a first roadside light emitter, and a roadside vehicle detector. A processor is configured to receive a signal from the roadside vehicle detector, command the first roadside light emitter to emit light according to a first pattern for a first duration, command the roadside imaging device to capture images of the side of the vehicle, and compute a vehicle occupancy, in each of the captured images by determining one or more regions of interest in each of the captured images, and determining a number of visible occupants in the one or more regions of interest. The processor determines a most likely number of occupants based on each determined vehicle occupancy.

## Claims

### Claim 1

A system for detecting occupancy of a vehicle travelling in an expected direction of travel along a road, the system comprising:
a first roadside imaging device positioned on a roadside, having a first field of view of the road, the first field of view incident on a side of the vehicle when the vehicle is on the road within the first field of view;
a first roadside light emitter emitting light towards vehicles in the first field of view;
a roadside vehicle detector;
a processor, in communication with a memory, configured to:
receive a signal from the roadside vehicle detector indicating that the vehicle is within the first field of view or proximate, relative to the expected direction of vehicle travel, to the first field of view;
command the first roadside light emitter to emit light according to a first pattern for a first duration;
command the first roadside imaging device to capture one or more images of the side of the vehicle according to a second pattern associated with the first pattern, during a second duration associated with the first duration;
receive the captured images of the side of the vehicle from the first roadside imaging device;
compute a vehicle occupancy of the vehicle by, in each of the captured images:
determining one or more regions of interest of the vehicle in each of the captured images;
determining the vehicle occupancy as a number of visible occupants in the one or more regions of interest; and
determining a most likely number of occupants based on each determined vehicle occupancy; and
transmit the vehicle occupancy to a monitoring system.

### Claim 2 (depends on 1)

The system of claim 1, wherein:
the first roadside imaging device is positioned to extract data for different perspectives of occupants as the vehicle travels horizontally across the field of view; and
each of the images captured by the first roadside imaging device include different perspectives of the side of the vehicle.

### Claim 3 (depends on 2)

The system of claim 2 wherein the processor is configured to compute a yaw angle relative to a horizontal axis perpendicular to the expected direction of vehicle travel, wherein the images captured by the first roadside imaging device include the different perspectives of the side of the vehicle based on the first yaw angle.

### Claim 4 (depends on 1)

The system of claim 1, wherein the processor, to compute the vehicle occupancy of the vehicle, is configured to:
discard uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and
determine the number of visible occupants based on determining one or more regions of interest of the vehicle in the respective subset of the plurality of captures images.

### Claim 5 (depends on 1)

The system of claim 1, wherein the first roadside imaging device, the first roadside light emitter, and the vehicle detector are attached to a mobile roadside structure.

### Claim 6 (depends on 1)

The system of claim 1, further comprising:
a second roadside imaging device, above the first roadside imaging device, the second roadside imaging device having a second field of view of a second lane of the road, the second lane being further from the first roadside imaging device than a first lane of the road, the second field of view incident on a side of a further vehicle when the further vehicle is in the second lane within the second field of view;
a second roadside light emitter adjacent to the road and emitting light towards vehicles in the second field of view;
wherein the processor is further configured to:
receive another signal from the vehicle detector indicating that the further vehicle is within or proximate, relative to the expected direction of vehicle travel, to the second field of view;
command the second roadside light emitter to emit light according to a third pattern for a third duration;
command the second roadside imaging device to capture additional images of the side of the further vehicle according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration;
receive the additional captured images of the side of the further vehicle from the second roadside imaging device;
compute a vehicle occupancy of the further vehicle by, in each of the additional captured images by:
determining one or more regions of interest of the further vehicle in each of the additional captured images;
determining the vehicle occupancy of the further vehicle as a number of visible occupants of the further vehicle in the one or more regions of interest of the further vehicle; and
determining a most likely number of occupants of the further vehicle based on each determined vehicle occupancy of the further vehicle; and
transmit the vehicle occupancy of the further vehicle to the monitoring system.

### Claim 7 (depends on 6)

The system of claim 6, wherein the first field of view and the second field of view overlap, and the processor is further configured to:
determine the one or more regions of interest of the vehicle in the one or more additional captured images;
determine a further number of visible occupants of the vehicle in the one or more additional captured images in the one or more regions of interest; and
determine the most likely number of occupants of the vehicle based on each determined vehicle occupancy and each determined further number of visible occupants.

### Claim 8 (depends on 1)

The system of claim 1, wherein the processor is further configured to:
monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and
adjust one or more parameters of the first roadside imaging device or the first light emitter into a determined optimal configuration for capturing vehicles travelling the expected vehicle speed.

### Claim 9 (depends on 1)

The system of claim 1, wherein the processor is further configured to:
monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and
determine the first pattern and the first time window based on the expected vehicle speed.

### Claim 10 (depends on 1)

The system of claim 1, further comprising:
a sensor for detecting ambient conditions;
wherein the processor is further configured to:
receive ambient condition information from the sensor;
determine an optimal configuration for the imaging device based on the received ambient condition; and
transmit a further command signal to the imaging device capture images according to the optimal configuration.

### Claim 11 (depends on 1)

The system of claim 1, wherein the light emitter is an LED emitting infrared or near infrared light, the first pattern is 120 pulses per second, and the regions of interest are a rear side window and a front side window.

### Claim 12 (depends on 11)

The method of claim 11 further comprising computing a correction parameter and providing visual guidance using augmented reality avatars on a display device.

### Claim 13

A method for detecting occupancy of a vehicle travelling in an expected direction of travel along a road, the method comprising;
receiving a signal indicating that the vehicle is within or proximate, relative to the expected direction of vehicle travel, to a first field of view of a first roadside imaging device;
commanding a first roadside light emitter to emit light according to a first pattern for a first duration;
commanding the first roadside imaging device to capture images of a side of the vehicle according to a second pattern associated with the first pattern, during a second duration associated with the first duration;
receiving the captured images of the side of the vehicle from the first roadside imaging device;
computing a vehicle occupancy of the vehicle by, in each of the captured images:
determining one or more regions of interest of the side of the vehicle in each of the captured images;
determining the vehicle occupancy in the one or more regions of interest; and
determining a most likely number of occupants based on each determined vehicle occupancy; and
transmitting the most likely number of occupants to a monitoring system.

### Claim 14 (depends on 13)

The method of claim 13, further comprising:
discarding uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and
determining the number of visible occupants based on determining one or more regions of interest of the vehicle in the respective subset of the plurality of captures images.

### Claim 15 (depends on 13)

The method of claim 13, wherein the one or more regions of interest include at least one of a rear side window and a front side window.

### Claim 16 (depends on 13)

The method of claim 13, wherein each of the captured images includes the side of the vehicle at different perspectives based on a yaw angle which encourages image variation.

### Claim 17 (depends on 13)

The method of claim 13, the method further comprising:
commanding a second roadside imaging device to capture additional images of the side of the vehicle from a second field of view according to a fourth pattern associated with the first pattern, for a fourth duration associated with the first duration;
receive the additional captured images of the side of the vehicle from the second roadside imaging device;
wherein computing the vehicle occupancy of the vehicle further comprises, for each of the additional captured images:
determining one or more additional regions of interest of the vehicle;
determining the vehicle occupancy of the vehicle in the additional one or more regions of interest of the vehicle; and
determining the most likely number of occupants of the vehicle based on the each of the number of visible occupants and the further number of visible occupants; and
transmitting the vehicle occupancy of the further vehicle to the monitoring system.

### Claim 18 (depends on 17)

The method of claim 17, the method further comprising:
receiving a signal indicating that a further vehicle is within or proximate, relative to the expected direction of vehicle travel, to the second field of view;
commanding a second roadside light emitter to emit light according to a third pattern for a third duration;
commanding the second roadside imaging device to capture additional images of a side of the further vehicle according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration;
receiving the additional captured images of the side of the vehicle from the first roadside imaging device;
computing a vehicle occupancy of the further vehicle by, in each of the additional captured images:
determining one or more further regions of interest of a side of the further vehicle in each of the additional captured images;
determining the further vehicle occupancy as a number of visible occupants in the one or more further regions of interest; and
determining a most likely number of occupants of the further vehicle based on each determined further vehicle occupancy; and
transmitting the most likely number of occupants of the further vehicle to the monitoring system.

### Claim 19 (depends on 13)

The method of claim 13, the method further comprising:
monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and
adjusting one or more parameters of the first roadside imaging device or the first light emitter into a determined adjusted configuration for capturing vehicles travelling the expected vehicle speed.

### Claim 20 (depends on 13)

The method of claim 13, the method further comprising:
monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and
determining the first pattern and the first time window based on the expected vehicle speed.