Patent ID: 12258024

Like reference numbers and designations in the various drawings indicate like elements.

DETAILED DESCRIPTION

The detailed description set forth below, in connection with the appended drawings, is intended as a description of various configurations and is not intended to limit the scope of the disclosure. Rather, the detailed description includes specific details for the purpose of providing a thorough understanding of the inventive subject matter. It will be apparent to those skilled in the art that these specific details are not required in every case and that, in some instances, well-known structures and components are shown in block diagram form for clarity of presentation.

The present disclosure provides systems, apparatus, methods, and computer-readable media that support driver monitoring and vehicle monitoring that may be used in smart vehicles and/or automated vehicles. In particular embodiments, the vehicle may monitor and score a user's attentiveness by determining high-risk portions of the surroundings and analyzing a user's gaze direction to determine whether the user is spending sufficient time in monitoring the high-risk portions of the surroundings while driving. The vehicle may alert the driver to missed high-risk areas, control the vehicle in the absence of response from the driver, and/or report the driver's score to a remote facility.

Particular implementations of the subject matter described in this disclosure may be implemented to realize one or more of the following potential advantages or benefits. In some aspects, the present disclosure provides techniques for improving safety of drivers operating vehicle systems and a reduction of vehicle collisions that result in damage to life and property.

FIG.1is a perspective view of a motor vehicle with a driver monitoring system according to embodiments of this disclosure. A vehicle100may include a front-facing camera112mounted inside the cabin looking through the windshield102. The vehicle may also include a cabin-facing camera114mounted inside the cabin looking towards occupants of the vehicle100, and in particular the driver of the vehicle100. Although one set of mounting positions for cameras112and114are shown for vehicle100, other mounting locations may be used for the cameras112and114. For example, one or more cameras may be mounted on one of the driver or passenger B pillars126or one of the driver or passenger C pillars128, such as near the top of the pillars126or128. As another example, one or more cameras may be mounted at the front of vehicle100, such as behind the radiator grill130or integrated with bumper132. As a further example, one or more cameras may be mounted as part of a driver or passenger side mirror assembly134.

The camera112may be oriented such that the field of view of camera112captures a scene in front of the vehicle100in the direction that the vehicle100is moving when in drive mode or forward direction. In some embodiments, an additional camera may be located at the rear of the vehicle100and oriented such that the field of view of the additional camera captures a scene behind the vehicle100in the direction that the vehicle100is moving when in reverse direction. Although embodiments of the disclosure may be described with reference to a “front-facing” camera, referring to camera112, aspects of the disclosure may be applied similarly to a “rear-facing” camera facing in the reverse direction of the vehicle100. Thus, the benefits obtained while the operator is driving the vehicle100in a forward direction may likewise be obtained while the operator is driving the vehicle100in a reverse direction.

Further, although embodiments of the disclosure may be described with reference a “front-facing” camera, referring to camera112, aspects of the disclosure may be applied similarly to an input received from an array of cameras mounted around the vehicle100to provide a larger field of view, which may be as large as 360 degrees around parallel to the ground and/or as large as 180 degrees around a vertical direction perpendicular to the ground. For example, additional cameras may be mounted around the outside of vehicle100, such as on or integrated in the doors, on or integrated in the wheels, on or integrated in the bumpers, on or integrated in the hood, and/or on or integrated in the roof.

The camera114may be oriented such that the field of view of camera114captures a scene in the cabin of the vehicle and includes the user operator of the vehicle, and in particular the face of the user operator of the vehicle with sufficient detail to discern a gaze direction of the user operator.

Each of the cameras112and114may include one, two, or more image sensors, such as including a first image sensor. When multiple image sensors are present, the first image sensor may have a larger field of view (FOV) than the second image sensor or the first image sensor may have different sensitivity or different dynamic range than the second image sensor. In one example, the first image sensor may be a wide-angle image sensor, and the second image sensor may be a telephoto image sensor. In another example, the first sensor is configured to obtain an image through a first lens with a first optical axis and the second sensor is configured to obtain an image through a second lens with a second optical axis different from the first optical axis. Additionally or alternatively, the first lens may have a first magnification, and the second lens may have a second magnification different from the first magnification. This configuration may occur in a camera module with a lens cluster, in which the multiple image sensors and associated lenses are located in offset locations within the camera module. Additional image sensors may be included with larger, smaller, or same fields of view.

Each image sensor may include means for capturing data representative of a scene, such as image sensors (including charge-coupled devices (CCDs), Bayer-filter sensors, infrared (IR) detectors, ultraviolet (UV) detectors, complimentary metal-oxide-semiconductor (CMOS) sensors), and/or time of flight detectors. The apparatus may further include one or more means for accumulating and/or focusing light rays into the one or more image sensors (including simple lenses, compound lenses, spherical lenses, and non-spherical lenses). These components may be controlled to capture the first, second, and/or more image frames. The image frames may be processed to form a single output image frame, such as through a fusion operation, and that output image frame further processed according to the aspects described herein.

As used herein, image sensor may refer to the image sensor itself and any certain other components coupled to the image sensor used to generate an image frame for processing by the image signal processor or other logic circuitry or storage in memory, whether a short-term buffer or longer-term non-volatile memory. For example, an image sensor may include other components of a camera, including a shutter, buffer, or other readout circuitry for accessing individual pixels of an image sensor. The image sensor may further refer to an analog front end or other circuitry for converting analog signals to digital representations for the image frame that are provided to digital circuitry coupled to the image sensor.

FIG.2shows a block diagram of an example image processing configuration for a vehicle according to one or more aspects of the disclosure. The processing system100may include, or otherwise be coupled to, an image signal processor212for processing image frames from one or more image sensors, such as a first image sensor201, a second image sensor202, and a depth sensor240. In some implementations, the vehicle100also includes or is coupled to a processor (e.g., CPU)204and a memory206storing instructions208. The processing system100may also include or be coupled to a display214and input/output (I/O) components216. I/O components216may be used for interacting with a user, such as a touch screen interface and/or physical buttons. I/O components216may also include network interfaces for communicating with other devices, such as other vehicles, an operator's mobile devices, and/or a remote monitoring system. The network interfaces may include one or more of a wide area network (WAN) adaptor252, a local area network (LAN) adaptor253, and/or a personal area network (PAN) adaptor254. An example WAN adaptor252is a 4G LTE or a 5G NR wireless network adaptor. An example LAN adaptor253is an IEEE 802.11 WiFi wireless network adapter. An example PAN adaptor254is a Bluetooth wireless network adaptor. Each of the adaptors252,253, and/or254may be coupled to an antenna, including multiple antennas configured for primary and diversity reception and/or configured for receiving specific frequency bands. The vehicle100may further include or be coupled to a power supply218, such as a battery or an alternator. The vehicle100may also include or be coupled to additional features or components that are not shown inFIG.2. In one example, a wireless interface, which may include one or more transceivers and associated baseband processors, may be coupled to or included in WAN adaptor252for a wireless communication device. In a further example, an analog front end (AFE) to convert analog image frame data to digital image frame data may be coupled between the image sensors201and202and the image signal processor212.

The vehicle100may include a sensor hub250for interfacing with sensors to receive data regarding movement of the vehicle100, data regarding an environment around the vehicle100, and/or other non-camera sensor data. One example non-camera sensor is a gyroscope, a device configured for measuring rotation, orientation, and/or angular velocity to generate motion data. Another example non-camera sensor is an accelerometer, a device configured for measuring acceleration, which may also be used to determine velocity and distance traveled by appropriately integrating the measured acceleration, and one or more of the acceleration, velocity, and or distance may be included in generated motion data. In further examples, a non-camera sensor may be a global positioning system (GPS) receiver, a light detection and ranging (LiDAR) system, a radio detection and ranging (RADAR) system, or other ranging systems.

The image signal processor (ISP)212may receive image data, such as used to form image frames. In one embodiment, a local bus connection couples the image signal processor212to image sensors201and202of a first camera203, which may correspond to camera112ofFIG.1, and second camera205, which may correspond to camera114ofFIG.1, respectively. In another embodiment, a wire interface may couple the image signal processor212to an external image sensor. In a further embodiment, a wireless interface may couple the image signal processor212to the image sensor201,202.

The first camera203may include the first image sensor201and a corresponding first lens231. The second camera205may include the second image sensor202and a corresponding second lens232. Each of the lenses231and232may be controlled by an associated autofocus (AF) algorithm233executing in the ISP212, which adjust the lenses231and232to focus on a particular focal plane at a certain scene depth from the image sensors201and202. The AF algorithm233may be assisted by depth sensor240.

The first image sensor201and the second image sensor202are configured to capture one or more image frames. Lenses231and232focus light at the image sensors201and202, respectively, through one or more apertures for receiving light, one or more shutters for blocking light when outside an exposure window, one or more color filter arrays (CFAs) for filtering light outside of specific frequency ranges, one or more analog front ends for converting analog measurements to digital information, and/or other suitable components for imaging.

In some embodiments, the image signal processor212may execute instructions from a memory, such as instructions208from the memory206, instructions stored in a separate memory coupled to or included in the image signal processor212, or instructions provided by the processor204. In addition, or in the alternative, the image signal processor212may include specific hardware (such as one or more integrated circuits (ICs)) configured to perform one or more operations described in the present disclosure. For example, the image signal processor212may include one or more image front ends (IFEs)235, one or more image post-processing engines (IPEs)236, and or one or more auto exposure compensation (AEC)234engines. The AF233, AEC234, IFE235, IPE236may each include application-specific circuitry, be embodied as software code executed by the ISP212, and/or a combination of hardware within and software code executing on the ISP212.

In some implementations, the memory206may include a non-transient or non-transitory computer readable medium storing computer-executable instructions208to perform all or a portion of one or more operations described in this disclosure. In some implementations, the instructions208include a camera application (or other suitable application) to be executed during operation of the vehicle100for generating images or videos. The instructions208may also include other applications or programs executed for the vehicle100, such as an operating system, mapping applications, or entertainment applications. Execution of the camera application, such as by the processor204, may cause the vehicle100to generate images using the image sensors201and202and the image signal processor212. The memory206may also be accessed by the image signal processor212to store processed frames or may be accessed by the processor204to obtain the processed frames. In some embodiments, the vehicle100includes a system on chip (SoC) that incorporates the image signal processor212, the processor204, the sensor hub250, the memory206, and input/output components216into a single package.

In some embodiments, at least one of the image signal processor212or the processor204executes instructions to perform various operations described herein, including object detection, risk map generation, driver monitoring, and driver alert operations. For example, execution of the instructions can instruct the image signal processor212to begin or end capturing an image frame or a sequence of image frames. In some embodiments, the processor204may include one or more general-purpose processor cores204A capable of executing scripts or instructions of one or more software programs, such as instructions208stored within the memory206. For example, the processor204may include one or more application processors configured to execute the camera application (or other suitable application for generating images or video) stored in the memory206.

In executing the camera application, the processor204may be configured to instruct the image signal processor212to perform one or more operations with reference to the image sensors201or202. For example, the camera application may receive a command to begin a video preview display upon which a video comprising a sequence of image frames is captured and processed from one or more image sensors201or202and displayed on an informational display in the cabin of the vehicle100.

In some embodiments, the processor204may include ICs or other hardware (e.g., an artificial intelligence (AI) engine224) in addition to the ability to execute software to cause the vehicle100to perform a number of functions or operations, such as the operations described herein. In some other embodiments, the vehicle100does not include the processor204, such as when all of the described functionality is configured in the image signal processor212.

In some embodiments, the display214may include one or more suitable displays or screens allowing for user interaction and/or to present items to the user, such as a preview of the image frames being captured by the image sensors201and202. In some embodiments, the display214is a touch-sensitive display. The I/O components216may be or include any suitable mechanism, interface, or device to receive input (such as commands) from the user and to provide output to the user through the display214. For example, the I/O components216may include (but are not limited to) a graphical user interface (GUI), a keyboard, a mouse, a microphone, speakers, a squeezable bezel, one or more buttons (such as a power button), a slider, a switch, and so on.

While shown to be coupled to each other via the processor204, components (such as the processor204, the memory206, the image signal processor212, the display214, and the I/O components216) may be coupled to each another in other various arrangements, such as via one or more local buses, which are not shown for simplicity. While the image signal processor212is illustrated as separate from the processor204, the image signal processor212may be a core of a processor204that is an application processor unit (APU), included in a system on chip (SoC), or otherwise included with the processor204. While the vehicle100is referred to in the examples herein for including aspects of the present disclosure, some device components may not be shown inFIG.2to prevent obscuring aspects of the present disclosure. Additionally, other components, numbers of components, or combinations of components may be included in a suitable vehicle for performing aspects of the present disclosure. As such, the present disclosure is not limited to a specific device or configuration of components, including the vehicle100.

The vehicle100may communicate as a user equipment (UE) within a wireless network300, such as through WAN adaptor252, as shown inFIG.3.FIG.3is a block diagram illustrating details of an example wireless communication system according to one or more aspects. Wireless network300may, for example, include a 5G wireless network. As appreciated by those skilled in the art, components appearing inFIG.3are likely to have related counterparts in other network arrangements including, for example, cellular-style network arrangements and non-cellular-style-network arrangements (e.g., device-to-device or peer-to-peer or ad-hoc network arrangements, etc.).

Wireless network300illustrated inFIG.3includes base stations305and other network entities. A base station may be a station that communicates with the UEs and may also be referred to as an evolved node B (eNB), a next generation eNB (gNB), an access point, and the like. Each base station305may provide communication coverage for a particular geographic area. In 3GPP, the term “cell” may refer to this particular geographic coverage area of a base station or a base station subsystem serving the coverage area, depending on the context in which the term is used. In implementations of wireless network300herein, base stations305may be associated with a same operator or different operators (e.g., wireless network300may include a plurality of operator wireless networks). Additionally, in implementations of wireless network300herein, base station305may provide wireless communications using one or more of the same frequencies (e.g., one or more frequency bands in licensed spectrum, unlicensed spectrum, or a combination thereof) as a neighboring cell. In some examples, an individual base station305or UE315may be operated by more than one network operating entity. In some other examples, each base station305and UE315may be operated by a single network operating entity.

A base station may provide communication coverage for a macro cell or a small cell, such as a pico cell or a femto cell, or other types of cell. A macro cell generally covers a relatively large geographic area (e.g., several kilometers in radius) and may allow unrestricted access by UEs with service subscriptions with the network provider. A small cell, such as a pico cell, would generally cover a relatively smaller geographic area and may allow unrestricted access by UEs with service subscriptions with the network provider. A small cell, such as a femto cell, would also generally cover a relatively small geographic area (e.g., a home) and, in addition to unrestricted access, may also provide restricted access by UEs having an association with the femto cell (e.g., UEs in a closed subscriber group (CSG), UEs for users in the home, and the like). A base station for a macro cell may be referred to as a macro base station. A base station for a small cell may be referred to as a small cell base station, a pico base station, a femto base station or a home base station. In the example shown inFIG.3, base stations305dand305eare regular macro base stations, while base stations305a-305care macro base stations enabled with one of three-dimension (3D), full dimension (FD), or massive MIMO. Base stations305a-305ctake advantage of their higher dimension MIMO capabilities to exploit 3D beamforming in both elevation and azimuth to increase coverage and capacity. Base station305fis a small cell base station which may be a home node or portable access point. A base station may support one or multiple (e.g., two, three, four, and the like) cells.

Wireless network300may support synchronous or asynchronous operation. For synchronous operation, the base stations may have similar frame timing, and transmissions from different base stations may be approximately aligned in time. For asynchronous operation, the base stations may have different frame timing, and transmissions from different base stations may not be aligned in time. In some scenarios, networks may be enabled or configured to handle dynamic switching between synchronous or asynchronous operations.

UEs315are dispersed throughout the wireless network300, and each UE may be stationary or mobile. It should be appreciated that, although a mobile apparatus is commonly referred to as a UE in standards and specifications promulgated by the 3GPP, such apparatus may additionally or otherwise be referred to by those skilled in the art as a mobile station (MS), a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communications device, a remote device, a mobile subscriber station, an access terminal (AT), a mobile terminal, a wireless terminal, a remote terminal, a handset, a terminal, a user agent, a mobile client, a client, a gaming device, an augmented reality device, vehicular component, vehicular device, or vehicular module, or some other suitable terminology.

Some non-limiting examples of a mobile apparatus, such as may include implementations of one or more of UEs315, include a mobile, a cellular (cell) phone, a smart phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a laptop, a personal computer (PC), a notebook, a netbook, a smart book, a tablet, a personal digital assistant (PDA), and a vehicle. Although UEs315a-jare specifically shown as vehicles, a vehicle may employ the communication configuration described with reference to any of the UEs315a-315k.

In one aspect, a UE may be a device that includes a Universal Integrated Circuit Card (UICC). In another aspect, a UE may be a device that does not include a UICC. In some aspects, UEs that do not include UICCs may also be referred to as IoE devices. UEs315a-315dof the implementation illustrated inFIG.3are examples of mobile smart phone-type devices accessing wireless network300. A UE may also be a machine specifically configured for connected communication, including machine type communication (MTC), enhanced MTC (eMTC), narrowband IoT (NB-IoT) and the like. UEs315e-315killustrated inFIG.3are examples of various machines configured for communication that access wireless network300.

A mobile apparatus, such as UEs315, may be able to communicate with any type of the base stations, whether macro base stations, pico base stations, femto base stations, relays, and the like. InFIG.3, a communication link (represented as a lightning bolt) indicates wireless transmissions between a UE and a serving base station, which is a base station designated to serve the UE on the downlink or uplink, or desired transmission between base stations, and backhaul transmissions between base stations. UEs may operate as base stations or other network nodes in some scenarios. Backhaul communication between base stations of wireless network300may occur using wired or wireless communication links.

In operation at wireless network300, base stations305a-305cserve UEs315aand315busing 3D beamforming and coordinated spatial techniques, such as coordinated multipoint (CoMP) or multi-connectivity. Macro base station305dperforms backhaul communications with base stations305a-305c, as well as small cell, base station305f. Macro base station305dalso transmits multicast services which are subscribed to and received by UEs315cand315d. Such multicast services may include mobile television or stream video, or may include other services for providing community information, such as weather emergencies or alerts, such as Amber alerts or gray alerts.

Wireless network300of implementations supports mission critical communications with ultra-reliable and redundant links for mission critical devices, such UE315e, which is a drone. Redundant communication links with UE315einclude from macro base stations305dand305e, as well as small cell base station305f. Other machine type devices, such as UE315f(thermometer), UE315g(smart meter), and UE315h(wearable device) may communicate through wireless network300either directly with base stations, such as small cell base station305f, and macro base station305e, or in multi-hop configurations by communicating with another user device which relays its information to the network, such as UE315fcommunicating temperature measurement information to the smart meter, UE315g, which is then reported to the network through small cell base station305f. Wireless network300may also provide additional network efficiency through dynamic, low-latency TDD communications or low-latency FDD communications, such as in a vehicle-to-vehicle (V2V) mesh network between UEs315i-315kcommunicating with macro base station305e.

Aspects of the vehicular systems described with reference to, and shown in,FIG.1,FIG.2, andFIG.3may be used to determine user operator attentiveness. For example, operator attentiveness, according to aspects of this disclosure, may be determined based on input received from the cameras112and114.FIG.4Ais a block diagram illustrating a system for determining operator attentiveness according to one or more aspects of the disclosure.

A region-of-interest (ROI) generator412may receive input from forward-facing camera402. The ROI generator412may process image frames captured by camera402to determine regions within the scene in a field of view of the camera402that captures a portion or all of the surroundings of a vehicle. The determined regions may be regions of interest because the regions should receive additional attention due to a high likelihood of a vehicle collision associated with the region. The ROI generator412outputs a set of regions of interest, which may be represented as a set of bounding box coordinates for the ROI. For some input scenes, there may be no region of interest such that the set is a null set, which may indicate there is no risk to assess for the operator. For example, a polygon with N number of points may be represented as N pairs of x and y coordinates corresponding to pixels within the image frame captured by camera402. In some embodiments, the ROI may be determined based on depth information received from a depth sensor or from another depth determination system such as a dual image sensor system. For example, the depth information may be used to separate objects by distance within the field of view of the front-facing camera402.

A gaze estimator414may receive input from inward-facing camera404. The gaze estimator414may process image frames captured by camera404to determine a direction of a user operator's gaze based on, for example, a location of the operator's pupils, a shape of the operator's pupils as captured in the image frame, and/or other facial features of the operator. The gaze estimator414outputs a gaze direction, which may be represented as a gaze vector. For example, a three-dimensional (3D) vector may be represented by three values corresponding to a magnitude in each of the x-, y-, and z-directions of a reference vector. In some embodiments, the gaze estimator414may also output a head position corresponding to an x,y or x,y,z position for the operator in the cabin of the vehicle.

A gaze analyzer422receives the gaze vector and the set of ROIs and correlates the operator's gaze to a particular portion of the field of view of the front-facing camera402. The gaze analyzer422may determine, based on the correlated gaze vector and the ROIs whether the operator has sufficiently viewed the scene in front of or around the vehicle. In some embodiments, this may involve determining whether the operator has viewed, and how much attention the operator has given to, each of the ROIs. For example, the gaze analyzer422may determine a dwell time that the operator's gaze direction corresponds to the ROI. If the dwell time is less than a certain threshold, the user may be determined to not be attentive enough to the ROI. In some embodiments, this may involve determining whether the operator has viewed a sufficient number of highest priority ROIs. In some embodiments, this may involve using artificial intelligence to compare the operator's behavior to the ROIs to determine whether the operator's behavior sufficiently checks the scene.

An output of the gaze analyzer422may be used to determine information regarding the operator, such as whether the operator is being appropriately attentive to high-risk regions in the path of the vehicle during operation of the vehicle. In some embodiments, the gaze analyzer422may output an attentiveness score reflecting one or more of a percentage of ROIs viewed by the operator and/or an amount of time the operator is gazing on the ROIs. The attentiveness score may indicate characteristics of the operator, such as whether the operator is drowsy or alert or whether the operator is skilled or unskilled. In some embodiments, the attentiveness score may be compared with a baseline score for the operator to separate operator skill from drowsiness.

In one example operation, an operator identification (ID) may be determined using facial recognition based on image data from the inward-facing camera404, the operator ID may be used to look up a corresponding operator profile with an average attentiveness score, and the output of the gaze analyzer422compared with the average attentiveness score. The operator may be determined to be drowsy when the determined attentiveness score is below the average attentiveness score by more than a threshold amount. The operator's profile may be updated over time to reflect changing skill level of the operator by updating the average attentiveness score with the determined attentiveness score.

A warning actuator432may receive an output of the gaze analyzer422and determine an appropriate operation to be performed within the vehicle. One or more criteria may be applied against the output of the gaze analyzer422, in which the criteria specify a condition(s) to be satisfied and an operation to execute based on matching the conditions. For example, the warning actuator432may determine the operator is drowsy and display an alert on a dashboard of the vehicle based on the operator's attentiveness score being below a threshold level (or a threshold below an expected value for the operator). As another example, the warning actuator432may control vehicle operations based on criteria, such as applying a speed limiter to the vehicle or initiating a safe-stop procedure when the operator is determined to be inattentive.

The warning actuator432may receive additional information from the gaze analyzer422, such as ROIs to which the operator is not or did not provide sufficient attention. For example, the gaze analyzer422may output an identifier of the ROI determined by ROI generator412, provide identifying information such as x,y coordinates for a ROI, and/or provide a marked-up version of the image frame captured by forward-facing camera402to annotate the missed ROI in the captured scene. The warning actuator432may output information to the operator indicating a missed ROI. In some embodiments, the warning actuator432may maintain a count of missed ROIs, and when the number of missed ROIs exceeds a threshold number within a certain time period the operator may be instructed to take a break and/or the vehicle controlled to enforce a break by disabling vehicle propulsion.

The warning actuator432may provide feedback to the user in addition to or in the alternative to a display output. For example, the warning actuator432may communicate with a haptic device in the operator's seat to activate vibration to provide tactile stimulation to the operator to make the operator more attentive. In some embodiments, when the vehicle approaches a threshold distance of an ROI without the user gazing at the ROI the operator's chair may vibrate to alert the operator to a potential danger. In some embodiments, a display in the cabin may also display an image of the scene around the car with the missed ROI highlighted in connection with the haptic feedback to draw the operator's attention to a particular ROT. In some embodiments, the haptic device may be part of a mobile device carried by the operator in their pocket with the warning actuator432interfacing with the mobile device through a wireless interface such as PAN adaptor254. In some embodiments, a heads-up display (HUD) may draw the operator's attention towards the missed ROI or otherwise where the operator's attention should be focused.

The warning actuator432may also communicate with other devices over a wireless communication system, such as that illustrated inFIG.3. For example, the warning actuator432may transmit the operator's attentiveness score and/or other information described with reference toFIG.4(including image data, ROI data, gaze vectors, marked-up image frames, etc.) to a remote monitoring station, a user device, a nearby vehicle, and/or other UEs.

In another embodiment, the gaze analyzer422may operate directly on the risk map as shown inFIG.4B.FIG.4Bis a block diagram illustrating a system for determining operator attentiveness according to one or more aspects of the disclosure. The gaze analyzer422receives a risk map output by risk map generator442, and compares the gaze vector to the risk map to determine an outcome of a set of criteria reflected in an attentiveness score. In an embodiment within the example ofFIG.4B, the gaze analyzer422may correlate the gaze direction directly with the probability distribution represented by a risk map.

FIG.5is a flow diagram illustrating an example process500that performs image processing in support of a vehicular monitoring operation according to one or more aspects. Operations of process500may be performed by a UE, such as a vehicle UE described above with reference toFIG.3orFIG.4. For example, example operations (also referred to as “blocks”) of process500may enable vehicle UE to support image processing and vehicle monitoring operations.

In block502, first image data from a first camera is received, the first image data representing a scene that includes the vehicle operator behavior. The first camera may be arranged to capture such first image data by being attached to a vehicle frame and pointing in a direction towards the driver seat. In some embodiments, the first camera may be configured to track a face of the operator to improve the reliability of gaze determinations made from the first image data.

In block504, second image data from a second camera is received, the second image data representing a scene that includes at least a portion of surroundings of the vehicle. The second camera may be arranged to capture such second image data by being attached to the vehicle frame and pointing in a direction away from the vehicle, which may be a different direction that the direction that the first camera is pointing. The second camera may be attached to the vehicle frame, for example, by attachment to a radiator grill, to a bumper, to a door, to a side-view mirror, to a hood, to a ceiling, to a wheel, to a windshield, or to an A, B, or C pillar.

In block506, a set of regions of interest is determined based on the second image data. A region of interest may reflect a region of the surroundings that is a high-risk area for operating the vehicle. An example high-risk area is a blocked view area, such as a parked vehicle or a blind corner, because an object may appear from behind the blocked view area without warning. An operator should be cautious of such high-risk areas and be actively checking the high-risk areas.

In block508, a gaze direction of the operator is determined based on the first image data. The first image may be analyzed to detect a face, identify eye portions of the face, and then determine a gaze direction based on the eye portions. For example, the eye portions of the image data may be adjusted for an angle of view from the camera such that the angle of the pupils with reference to the surroundings of the vehicle may be determined.

In block510, the gaze direction may be compared with the regions of interest to determine an attentiveness score. In some embodiments, the attentiveness score may be a binary value (e.g., yes or no) indicating whether the operator has checked the region of interest for a sufficient amount of time (e.g., total dwell time of all gazing or number of times the gaze direction returns to the region of interest) to safely pass through the high-risk region. In some embodiments, the attentiveness score may be a scaled value from1to10or1to100indicating an attentiveness rating based on the correspondence between the gaze direction and regions of interest determined over a period of time.

In certain embodiments, rules specifying criteria and outcomes may be applied to the attentiveness score. For example, a criterion may be that the attentiveness core is below a threshold level and the outcome may be to perform an action to alert the operator of their attentiveness score. The processing system may also take other action in the vehicle to reduce the consequences of low attentiveness or to improve the operator's attentiveness. For example, the processing system may begin to reduce the vehicle speed, place a limit on the vehicle speed, or prohibit propulsion of the vehicle. As another example, the processing system may flash interior lights and/or provide haptic feedback to the operator to increase the operator's alertness.

In certain embodiments, the rules may provide escalating response to operator inattentiveness, such as by increasing the severity of actions if less severe actions are not successful for improving attentiveness. For example, an initial warning may be presented on the dashboard, which if unsuccessful, may result in application of haptic feedback, which if unsuccessful, may result in applying brakes to stop the vehicle. The escalation of events may be ended when the operator's gaze is detected toward the region of interest.

In certain embodiments, the attentiveness score may be transmitted through a wireless communication network such as shown inFIG.3. The transmitted score may be used, for example, to record a history of the operator's driving behavior. The transmitted score may be used, for example, to warn nearby pedestrians through communication to the UE of the inattentive operator, to warn nearby officials through communication to the police's UE of the inattentive operator, and/or to warn nearby vehicles of the inattentive operator such that other operators may consider the vehicle to be a high-risk region of interest.

Example techniques for determining a region of interest as described in block506are shown inFIG.6AandFIG.6B.FIG.6Ais a block diagram illustrating a region of interest generator using an object detector according to one or more aspects. In ROI detector412ofFIG.6A, an object detector602may receive image data and/or depth data to detect objects in the surroundings of the vehicle. The objects may be provided to an object classifier604, which classifies the objects into categories such as car, person, trash can, bicycle, animal, etc. The list of objects detected by detector602and their classification determined by classifier604may be provided to risk modeler606. Risk modeler606may determine from the object's location in the surroundings and classification whether the object or the vicinity of the object represents a risk to the vehicle. Regions of the surroundings may be identified as regions of interest and output from the ROI detector by the risk modeler606. The ROI output may be a set of coordinates specifying a polygon in an image frame of the image data, such as a rectangle, that encloses an area of the image frame to indicate a high-risk area. The ROI output may alternatively be a single point in the image frame.

A region of interest may also be determined using a risk map, which is a two-dimensional or three-dimensional data structure of values representing surroundings of the vehicle and perceived risk to vehicle operation at various positions in the surroundings.FIG.6Bis a block diagram illustrating a region of interest generator using a risk map according to one or more aspects. A machine learning model may be trained offline and deployed in the vehicle as a risk map generator, such as within the ROI identifier616, which, during the operation of the vehicle by the operator, may generate a risk map based on one or more of image data, depth data, and vehicle state. The trained model may be generated from data collected from vehicles during operation, which may include image data, depth data, and/or other sensor data.

The risk map may be used by ROI identifier616to determine regions of interest from the risk map that the operator should be monitoring for safety reasons.

Although depth data is described as an optional input to the ROI detector412for detecting objects inFIG.6Aor determining a risk map inFIG.6B, other or additional data may be used in place of or in addition to the image data or depth data. For example, the ROI detector412may use input from one or more sensors of different modalities, e.g., cameras, radars, or lidars. In certain embodiments, the ROI detector412may use data obtained from the cloud or other vehicles in the vicinity.

Example high-risk regions of interests to be detected by the ROI detector412are shown inFIG.7.FIG.7is an illustration of a scene with high-risk regions that may be reflected in a risk map according to one or more aspects. A vehicle100driving down a street may have an obstructed view due to stationary object702and/or moving object704. Each of the objects702and704may thus create regions of interest712and714, respectively, to which an operator of the vehicle100should approach cautiously. For example, the operator should visually inspect the areas in the regions of interest712and714more frequently than other areas and/or approach the street areas corresponding to the regions of interest712and714slowly due to the possibility of an unseen pedestrian722crossing out in front of the vehicle100. If the user does not gaze in the direction of regions of interest712and714, the vehicle100may alert the user or take action to slow the vehicle100as the vehicle100approaches the regions of interest712and714, and then allow the vehicle to return to normal speed after passing the regions of interest712and714.

One example of such an operator alert is shown inFIG.8.FIG.8is an illustration of a vehicular display showing an alertness alert according to one or more aspects. An operator of the vehicle100may have view of a display802on a dashboard of the vehicle. The dashboard, or other display such as a heads-up display (HUD), of the vehicle100may display a representation of the vehicle surroundings, such as the image data from the front-facing camera and/or the generated scene model of the surroundings. The vehicle may display alerts804corresponding to the regions of interest that have been detected but that the operator has not sufficiently examined. The alerts804may grow in urgency as the vehicle100approaches the corresponding regions of interest, such as by changing color and/or blinking and/or increasing in intensity. The alerts804may be cleared when the operator sufficiently gazes in the direction of the corresponding region of interest.

It is noted that one or more blocks (or operations) described with reference toFIG.5may be combined with one or more blocks (or operations) described with reference to another of the figures. For example, one or more blocks (or operations) ofFIG.5may be combined with one or more blocks (or operations) ofFIG.3. As another example, one or more blocks associated withFIG.5may be combined with one or more blocks associated withFIG.2. As another example, one or more blocks associated withFIG.5may be combined with one or more blocks (or operations) associated withFIGS.6-8. Additionally, or alternatively, one or more operations described above with reference toFIGS.1-3may be combined with one or more operations described with reference toFIGS.4-8.

In one or more aspects, techniques for supporting vehicular operations may include additional aspects, such as any single aspect or any combination of aspects described below or in connection with one or more other processes or devices described elsewhere herein. In a first aspect, supporting image processing, such as for vehicular monitoring operations, may include an apparatus comprising one or more of a vehicle frame; a first camera attached to the vehicle frame and arranged to capture a first field of view comprising a portion of a cabin enclosed on at least some sides by the vehicle frame; a second camera attached to the vehicle frame and arranged to capture a second field of view corresponding to at least a portion of surroundings of the vehicle frame; and a processing system coupled to the first camera and to the second camera. Additionally, the apparatus may perform or operate according to one or more aspects as described below. In some implementations, the apparatus includes a wireless device, such as a UE. In some implementations, the apparatus may include at least one processor, and a memory coupled to the processor. The processor may be configured to perform operations described herein with respect to the apparatus. In some other implementations, the apparatus may include a non-transitory computer-readable medium having program code recorded thereon and the program code may be executable by a computer for causing the computer to perform operations described herein with reference to the apparatus. In some implementations, the apparatus may include one or more means configured to perform operations described herein. In some implementations, a method of wireless communication may include one or more operations described herein with reference to the apparatus.

In a second aspect, in combination with the first aspect, a processing system of the apparatus is configured to perform operations including receiving first image data from a first camera oriented in a first direction with a first field of view facing a user; receiving second image data from a second camera oriented in a second direction different from the first direction, the second camera having a second field of view corresponding to a field of view of the user; determining a region of interest based on the second image data; determining a gaze direction of the user based on the first image data; and determining an attentiveness score based on correspondence between the region of interest and the gaze direction.

In a third aspect, in combination with one or more of the first aspect or the second aspect, the first image data comprises a first plurality of image frames captured over a duration of time, and wherein the second image data comprises a second plurality of image frames captured over the duration of time.

In a fourth aspect, in combination with one or more of the first aspect through the third aspect, determining the attentiveness score comprises determining a fraction of the duration of time that the gaze direction of the user is correlated with the region of interest.

In a fifth aspect, in combination with one or more of the first aspect through the fourth aspect, determining the region of interest comprises: determining a risk map based on the second image data, wherein the region of interest corresponds to a portion of the risk map above a threshold risk level.

In a sixth aspect, in combination with one or more of the first aspect through the fifth aspect, determining the risk map comprises determining a risk associated with a scene model using a machine learning (ML) algorithm.

In a seventh aspect, in combination with one or more of the first aspect through the sixth aspect, determining the region of interest comprises: determining an object of interest in the second image data based on object detection, wherein the region of interest corresponds to the object of interest.

In an eighth aspect, in combination with one or more of the first aspect through the seventh aspect, the apparatus is also configured to perform operations including determining whether the attentiveness score meets a first criteria; and when the attentiveness score meets the first criteria, performing an action to alert the user.

In a ninth aspect, in combination with one or more of the first aspect through the eighth aspect, determining whether the attentiveness score meets a first criteria comprises determining whether the attentiveness score is a predetermined threshold amount below a historical attentiveness score corresponding to the user.

In a tenth aspect, in combination with one or more of the first aspect through the ninth aspect, performing the action to alert the user comprises displaying the second image data on a user display with the region of interest marked on the second image data.

In an eleventh aspect, in combination with one or more of the first aspect through the tenth aspect, the apparatus is also configured to perform operations including transmitting the attentiveness score through a wireless communication link.

Those of skill in the art would understand that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

Components, the functional blocks, and the modules described herein with respect toFIGS.1-8include processors, electronics devices, hardware devices, electronics components, logical circuits, memories, software codes, firmware codes, among other examples, or any combination thereof. Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, application, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, and/or functions, among other examples, whether referred to as software, firmware, middleware, microcode, hardware description language or otherwise. In addition, features discussed herein may be implemented via specialized processor circuitry, via executable instructions, or combinations thereof.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure. Skilled artisans will also readily recognize that the order or combination of components, methods, or interactions that are described herein are merely examples and that the components, methods, or interactions of the various aspects of the present disclosure may be combined or performed in ways other than those illustrated and described herein.

The various illustrative logics, logical blocks, modules, circuits and algorithm processes described in connection with the implementations disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. The interchangeability of hardware and software has been described generally, in terms of functionality, and illustrated in the various illustrative components, blocks, modules, circuits and processes described above. Whether such functionality is implemented in hardware or software depends upon the particular application and design constraints imposed on the overall system.

The hardware and data processing apparatus used to implement the various illustrative logics, logical blocks, modules and circuits described in connection with the aspects disclosed herein may be implemented or performed with a general purpose single- or multi-chip processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, or, any conventional processor, controller, microcontroller, or state machine. In some implementations, a processor may be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. In some implementations, particular processes and methods may be performed by circuitry that is specific to a given function.

In one or more aspects, the functions described may be implemented in hardware, digital electronic circuitry, computer software, firmware, including the structures disclosed in this specification and their structural equivalents thereof, or in any combination thereof. Implementations of the subject matter described in this specification also may be implemented as one or more computer programs, that is one or more modules of computer program instructions, encoded on a computer storage media for execution by, or to control the operation of, data processing apparatus.

If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. The processes of a method or algorithm disclosed herein may be implemented in a processor-executable software module which may reside on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that may be enabled to transfer a computer program from one place to another. A storage media may be any available media that may be accessed by a computer. By way of example, and not limitation, such computer-readable media may include random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that may be used to store desired program code in the form of instructions or data structures and that may be accessed by a computer. Also, any connection may be properly termed a computer-readable medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media. Additionally, the operations of a method or algorithm may reside as one or any combination or set of codes and instructions on a machine readable medium and computer-readable medium, which may be incorporated into a computer program product.

Various modifications to the implementations described in this disclosure may be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to some other implementations without departing from the spirit or scope of this disclosure. Thus, the claims are not intended to be limited to the implementations shown herein, but are to be accorded the widest scope consistent with this disclosure, the principles and the novel features disclosed herein.

Certain features that are described in this specification in the context of separate implementations also may be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation also may be implemented in multiple implementations separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination may in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. Further, the drawings may schematically depict one or more example processes in the form of a flow diagram. However, other operations that are not depicted may be incorporated in the example processes that are schematically illustrated. For example, one or more additional operations may be performed before, after, simultaneously, or between any of the illustrated operations. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the implementations described above should not be understood as requiring such separation in all implementations, and it should be understood that the described program components and systems may generally be integrated together in a single software product or packaged into multiple software products. Additionally, some other implementations are within the scope of the following claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve desirable results.

The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.