Vehicle control functionality

Abstract

Systems and techniques for providing vehicle control functionality of a vehicle are disclosed. For example, a computing device may determine a field of view (FOV) of a driver of a vehicle based on driver sensor data. The computing device may compare the driver's FOV to a predetermined threshold of the driver's FOV. The computing device may determine a reduced FOV of the driver based on the FOV of the driver being less than a predetermined threshold of the FOV of the driver. The computing device may determine one or more objects relative to the vehicle based on the traffic sensor data. The computing device may limit an amount of possible acceleration of the vehicle based on determining a reduced FOV of the driver and one or more objects relative to the vehicle.

Description

TECHNICAL FIELD

[0001] The present disclosure relates generally to driving assistance systems. For example, aspects of the present disclosure relate to vehicle control functions (e.g., acceleration functions) of a vehicle. BACKGROUND

[0002] Vehicles come in many shapes and sizes, are propelled by various propulsion technologies, and carry cargo including people, animals, or objects. These machines are capable of moving cargo long distances, moving cargo at high speeds, and moving more cargo than a human can. Vehicles were originally piloted by humans to control the speed and direction of the cargo to a destination. Human operation of vehicles has resulted in many unfortunate accidents caused by collisions of vehicles with vehicles, vehicles with objects, vehicles with humans, or vehicles with animals. As research into vehicle automation has progressed, a variety of driving assistance systems have been produced and introduced. These driving assistance systems include: navigation guidance by GPS, adaptive cruise control, lane change assist, collision avoidance systems, night vision, parking assist, and blind spot detection. SUMMARY

[0003] The following presents a simplified summary relating to one or more aspects disclosed herein. Thus, the following summary should not be considered an extensive overview relating to all contemplated aspects, nor should the following summary be considered to identify key or critical elements relating to all contemplated aspects or to delineate the scope associated with any particular aspect. Accordingly, the following summary is merely a refinement in summary form of a number of concepts relating to one or more aspects as disclosed herein.

[0004] Systems, apparatuses, methods, and computer-readable media for vehicle control functions (e.g., acceleration functions for limiting acceleration and / or speed of a vehicle in certain scenarios) are disclosed. According to at least one example, a method for enabling vehicle acceleration control is provided. The method includes determining, by one or more processors of a vehicle and based on driver sensor data, a field of view (FOV) of a driver of the vehicle, determining, by the one or more processors and based on a FOV threshold, that the FOV of the driver is limited, wherein the FOV threshold is one of a predetermined threshold angle of the FOV of the driver or a percentage of the predetermined threshold angle of the FOV of the driver, detecting, by the one or more processors of the vehicle and based on traffic sensor data, one or more objects within a threshold distance relative to the vehicle, and controlling, by the one or more processors of the vehicle, an amount of possible acceleration or speed of the vehicle based on determining that the FOV of the driver is limited and detecting the one or more objects within the threshold distance.

[0005] In another illustrative example, an apparatus for enabling vehicle acceleration control of a vehicle is provided. The apparatus comprises at least one memory and at least one processor coupled to the at least one memory and configured to: determine a field of view (FOV) of a driver of the vehicle based on driver sensor data; determine that the FOV of the driver is limited based on a FOV threshold, wherein the FOV threshold is one of a predetermined threshold angle of the FOV of the driver or a percentage of the predetermined threshold angle of the FOV of the driver; detect one or more objects within a threshold distance relative to the vehicle based on traffic sensor data; and control an amount of possible acceleration or speed of the vehicle based on determining that the FOV of the driver is limited and detecting the one or more objects within the threshold distance.

[0006] In another illustrative example, a non-transitory computer-readable storage medium of a vehicle includes instructions stored thereon that, when executed by at least one processor, cause the at least one processor to: determine a field of view (FOV) of a driver of the vehicle based on driver sensor data; determine that the FOV of the driver is limited based on a FOV threshold, wherein the FOV threshold is one of a predetermined threshold angle of the FOV of the driver or a percentage of the predetermined threshold angle of the FOV of the driver; detect one or more objects within a threshold distance relative to the vehicle based on traffic sensor data; and control an amount of possible acceleration or speed of the vehicle based on determining that the FOV of the driver is limited and detecting the one or more objects within the threshold distance.

[0007] In another illustrative example, an apparatus comprises: means for determining, by one or more processors of a vehicle and based on driver sensor data, a field of view (FOV) of a driver of the vehicle; means for determining, by the one or more processors and based on a FOV threshold, that the FOV of the driver is limited, wherein the FOV threshold is one of a predetermined threshold angle of the FOV of the driver or a percentage of the predetermined threshold angle of the FOV of the driver; means for detecting, by the one or more processors of the vehicle and based on traffic sensor data, one or more objects within a threshold distance relative to the vehicle; and means for controlling, by the one or more processors of the vehicle, an amount of possible acceleration or speed of the vehicle based on determining that the FOV of the driver is limited and detecting the one or more objects within the threshold distance.

[0008] Aspects generally include methods, apparatus, systems, computer program products, non-transitory computer readable media, user equipment, wireless communication devices, and / or processing systems as substantially described with reference to and as illustrated by the drawings and specification.

[0009] In some aspects, one or more of the apparatuses described herein is a vehicle (e.g., a car, a truck, etc., or a component or system of a car, a truck, etc.), a mobile device (e.g., a mobile telephone or so-called “smart phone” or other mobile device), a wearable device, an extended reality device (e.g., a virtual reality (VR) device, an augmented reality (AR) device, or a mixed reality (MR) device), a personal computer, a laptop computer, a server computer, a robotic device, or other device, is part of them, or includes them. In some aspects, the apparatus includes a radio detection and ranging (radar) for capturing radio frequency (RF) signals. In some aspects, the apparatus includes one or more light detection and ranging (LiDAR) sensors, radar sensors, or other light-based sensors for capturing light-based (e.g., light frequency) signals. In some aspects, the apparatus includes one or more cameras for capturing one or more images. In some aspects, the apparatus further includes a display for displaying one or more images, notifications, and / or other displayable data. In some aspects, the apparatus described above can include one or more sensors that can be used to determine a location of the apparatus, a state of the apparatus (e.g., temperature, humidity level, and / or other state), and / or for other purposes.

[0010] Some aspects include an apparatus having a processor configured to perform one or more operations of any of the methods summarized above. Further aspects include a processing apparatus configured for use in an apparatus, the processing apparatus configured with processor-executable instructions to perform operations of any of the methods summarized above. Further aspects include a non-transitory processor-readable storage medium having stored thereon processor-executable instructions configured to cause a processor of an apparatus to perform operations of any of the methods summarized above. Further aspects include an apparatus having means for performing the functions of any of the methods summarized above.

[0011] The features and technical advantages of the examples according to this disclosure have been summarized quite extensively above in order to better understand the detailed description below. Additional features and advantages will be described below. The disclosed concepts and specific examples can be readily utilized as the basis for modifying or designing other structures for achieving the same purpose of this disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein (both their organization and operation) and their associated advantages will be better understood from the following description when considered in conjunction with the accompanying drawings. Each figure in the drawings is provided for illustrative and descriptive purposes and not as a definition of limitation of the claims. The foregoing, as well as other features and aspects, will become more apparent upon reference to the following specification, claims, and appended drawings.

[0012] This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to determine the scope of the claimed subject matter alone. This subject matter should be understood in conjunction with the appropriate portions of the entire specification of this patent, any or all of the accompanying drawings, and each claim.

[0013] Based on the accompanying drawings and detailed description, other objects and advantages associated with the aspects disclosed herein will be apparent to those skilled in the art. Attached Figure Description

[0014] The exemplary aspects of this application are described in detail below with reference to the following figures: Figure 1 This is a perspective view illustrating an example of a motor vehicle with a driver monitoring system according to some aspects of this disclosure.

[0015] Figure 2 This is a block diagram illustrating an example of an image processing configuration for a vehicle according to some aspects of this disclosure.

[0016] Figure 3 This is an illustration of an example of a vehicle parked at the intersection of two roads, according to some aspects of this disclosure.

[0017] Figure 4 This is an illustration of an example scenario of a driver with a different field of view (FOV) according to some aspects of this disclosure.

[0018] Figure 5 This is a flowchart illustrating an example of a detailed process for enabling acceleration functionality according to some aspects of this disclosure.

[0019] Figure 6 This is a flowchart illustrating an example of a detailed process for disabling an acceleration function according to some aspects of this disclosure.

[0020] Figure 7 is a flowchart illustrating an example of a process for enabling acceleration functionality according to some aspects of the present disclosure.

[0021] Figure 8 is a flowchart illustrating an example of a process for disabling acceleration functionality according to some aspects of the present disclosure.

[0022] Figure 9 An example computing system according to aspects of the present disclosure is illustrated. DETAILED DESCRIPTION

[0023] For illustrative purposes, certain aspects of the present disclosure are provided below. Alternative aspects can be devised without departing from the scope of the present disclosure. Additionally, well-known elements of the present disclosure, related to those described below, can not be described or will be omitted so as to not obscure the relevant details of the described aspects. Some aspects described herein can be independently applied and others can be applied in combination. These and other aspects, which can be appreciated by one of ordinary skill in the art, are described in further detail in the following description and accompanying drawings.

[0024] The following description provides example aspects only and is not intended to limit the scope, applicability or configuration of the disclosure. Rather, the following description of the example aspects will provide those skilled in the art with an enabling description of how the example aspects can be implemented. It should be understood that various changes can be made in the function and arrangement of elements without departing from the spirit and scope of the application as set forth in the appended claims.

[0025] The terms “exemplary” and / or “example” are used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” and / or “example” is not necessarily to be construed as preferred or advantageous over other aspects. Likewise, the term “aspects of the disclosure” does not require that all aspects of the disclosure include the discussed feature, advantage or mode of operation.

[0026] Driver behavior such as driver distraction is a key factor in most traffic accidents. Vehicles operated by distracted drivers can often result in collisions with other vehicles, vulnerable road users (VRUs) (e.g., pedestrians), or other objects. Traffic accidents involving vehicles colliding with VRUs such as bicyclists or pedestrians crossing an intersection can often result in injuries or fatalities.

[0027] To avoid such collisions, vehicles are often implemented with automatic emergency braking (AEB) functionality. AEB is an advanced driver assistance system (ADAS) that provides automatic braking based on sensor data to assist the driver in avoiding a collision. The sensor data can be obtained by sensors installed on the vehicle, such as cameras, radar sensors, and / or light detection and ranging (LiDAR) sensors. AEB can be triggered when the vehicle determines, based on the sensor data, that a collision is imminent and the driver does not react quickly enough to avoid the collision. When triggered, AEB will automatically engage the emergency brakes in the vehicle, which can cause the vehicle to come to a sudden stop. AEB is often equipped with forward collision warning (FCW) functionality. FCW can be used to alert the driver of a dangerous driving situation. When triggered, FCW can use lights (e.g., display colored warning lights and / or text warnings), sound (e.g., audio sounds and / or warning messages), and / or vibrations (e.g., seat and / or steering wheel vibrations) to draw the driver’s attention.

[0028] AEB can be triggered in a variety of different driving scenarios. In one example driving scenario, a vehicle can be stopped at an intersection of a road. If the driver of the vehicle becomes distracted (e.g., by engaging in a secondary task, such as looking at their smartphone), the driver’s attention can be directed to a narrower field of view than if the driver were not distracted. When the driver’s attention is directed to this narrower field of view, the risk of the driver failing to detect an object (e.g., a VRU, such as a pedestrian, other vehicle, etc.) approaching and / or entering the intersection can increase. This type of driving scenario often presents a need for the driver or vehicle to perform an emergency braking maneuver. When the vehicle performs AEB, the emergency brakes will be engaged to cause the vehicle to come to a sudden stop. This sudden stop can cause the driver to experience a sudden, jarring, jolting movement, which can reduce trust in the vehicle’s risk detection assistance systems and can significantly decrease the comfort and enjoyment of the driver’s driving experience. Thus, improved systems and techniques for assisting the driver in avoiding a collision while reducing the amount of jarring movement from AEB intervention can be beneficial.

[0029] In one or more aspects of the disclosure, systems, apparatuses, methods (also referred to as processes), and computer-readable media (collectively referred to herein as “systems and techniques”) are described herein that provide vehicle control functionality. For example, the systems and techniques can provide vehicle acceleration control (e.g., acceleration functionality to limit acceleration in certain scenarios and / or speed functionality to limit the speed of the vehicle in certain scenarios) of a vehicle. In one or more examples, vehicle acceleration control can be enabled without braking due to detection of an object (e.g., a VRU, other vehicle, etc.) approaching and / or entering an area (e.g., an intersection, parking lot, lane, or other area where the vehicle is stopped), determination of driver distraction (e.g., due to reduced or limited driver field of view), and in some cases, driver intent to move (e.g., evidenced by release of the brake or depression of the gas pedal).

[0030] In some aspects, when an object (e.g., a VRU, other vehicle, etc.) is detected relative to a vehicle (e.g., detected within a threshold distance from the vehicle, such as within five feet, ten feet, or other threshold distance, detected as approaching or moving toward the vehicle, detected as moving relative to the vehicle), such as when an object is detected as entering an area (e.g., an intersection, parking lot, lane, etc.) while the vehicle is stationary in the area (e.g., stopped at an intersection, waiting at a stoplight or stop sign, etc.), a limited acceleration or speed (e.g., such that the maximum possible acceleration is limited) can be triggered or applied for the vehicle. In some examples, the object relative to the vehicle can be notified to the driver (e.g., via an FCW). When the driver is no longer distracted (e.g., the driver is looking in many directions) and thus the driver’s field of view is restored, the acceleration or speed limit can be removed. Examples are described herein using an intersection as an example of an area where the acceleration or speed functionality can be applied. However, the systems and techniques can be applied to other types of areas, such as a parking lot, a lane, a drive through, etc.

[0031] In one or more examples, during operations to enable vehicle acceleration or speed control (e.g., when the vehicle is stopped in an area such as at an intersection), one or more driver sensors of the vehicle can sense a gaze (and / or head pose, such as a head of a user in a lowered head position) of a driver of the vehicle to produce driver sensor data. In one or more examples, the one or more driver sensors can be mounted within a passenger compartment of the vehicle and can include a camera. The driver sensor data including the gaze (and / or head pose, e.g., head position and orientation) of the driver can be stored in a memory of the vehicle.

[0032] One or more processors of a vehicle (e.g., of a driver monitoring system (DMS)) can determine a field of view (FOV) of a driver of the vehicle based on driver sensor data (e.g., based on a gaze of the driver and, in some cases, based on a head pose of the driver). In one or more examples, the one or more processors of the vehicle can compare the FOV of the driver to a predetermined threshold of the FOV. The one or more processors of the vehicle can determine a reduced or limited FOV of the driver (e.g., a narrow FOV, which can indicate a distracted driver) based on the FOV of the driver being less than the predetermined threshold of the FOV. In one or more examples, the predetermined threshold of the FOV can be a predetermined threshold angle of the FOV of the driver or a percentage of a predetermined threshold angle of the FOV of the driver.

[0033] In some cases, a predetermined threshold can be used to determine a non-limited FOV and a limited FOV. For example, in such cases, the predetermined threshold can be a threshold number of driver gazes (or saccades) that fall within a particular FOV. For example, if a driver performs a number of gazes (or saccades) within a particular FOV that is greater than the threshold number of driver gazes, the one or more processors can assign the particular FOV to the driver. In such cases, if the one or more processors determine that the user performs a number of gazes (or saccades) within a full FOV that is below the threshold (e.g., the driver saccades too little or not at all to the sides of the full FOV), the one or more processors can determine that the user has a limited FOV.

[0034] In some examples, the one or more processors of the vehicle can determine (e.g., assume) a reduced or limited FOV of the driver based on a head pose and eye gaze of the driver. For example, the one or more processors of the vehicle can determine, based on driver sensor data, that a head of the driver is rotated such that the driver is not looking at the road for a certain period of time (e.g., the driver’s eyes are averted from the road) (e.g., the head of the driver is in an averted position) (such as when the head of the driver is in a downward position). In such an example, the gaze of the driver is narrowed and the head pose of the driver is oriented away from a forward position (e.g., looking down instead of forward through the windshield), indicating a limited FOV. The one or more processors of the vehicle can compare the certain period of time that the driver is not looking at the road to a predetermined threshold amount of time (e.g., that the driver’s eyes are averted from the road). The one or more processors of the vehicle can determine (e.g., assume) a reduced or limited FOV of the driver based on the certain amount of time being greater than or equal to a threshold amount of time that the head of the driver is in the averted position.

[0035] In some examples, one or more processors of the vehicle can determine (e.g., assume) a reduced or limited FOV of the driver based on detecting that the user is engaged in an activity other than driving. For example, the one or more processors can determine that the driver has a limited FOV in response to detecting that the driver is operating a mobile device (e.g., a cell phone). In some cases, the one or more processors can determine that the driver has a limited FOV in response to detecting, by processing driver sensor data (e.g., one or more images captured using one or more cameras) captured using one or more driver sensors, that the driver is engaged in an activity other than driving. For example, a computer vision and / or machine learning model (e.g., a classification neural network) can process one or more images to detect an object (e.g., a mobile phone) in the one or more images, and can determine that the user is interacting with the object (e.g., operating the mobile phone) based on detecting the object in the one or more images. In response, the one or more processors can determine that the driver has a limited FOV.

[0036] One or more traffic sensors of the vehicle (e.g., mounted on or integrated with the vehicle) can sense an environment of the vehicle to produce traffic sensor data. In one or more examples, the one or more traffic sensors can include a camera, a radar sensor, an infrared sensor, and / or a LiDAR sensor. One or more processors of the vehicle can detect, based on the traffic sensor data, one or more objects relative to the vehicle, such as objects within a threshold distance relative to the vehicle, objects moving relative to the vehicle, objects that are approaching the vehicle (e.g., approaching a side and / or front of the vehicle), and / or the like. In some aspects, the vehicle can obtain traffic sensor data from one or more other vehicles or from one or more roadside units (RSUs). RSUs are devices that can send and receive messages to and from one or more vehicles, other RSUs, base stations, and / or the like over a communication link or interface (e.g., a cellular-based sidelink or PC5 interface, an 802.11 or WiFi-based dedicated short-range communications (DSRC) interface, and / or other interfaces). Examples of messages that can be sent and received by RSUs include vehicle-to-everything (V2X) messages. RSUs can be located on various transportation infrastructure systems, including traffic lights, roads, bridges, parking lots, tollbooths, and / or other infrastructure systems. In some examples, RSUs can facilitate communication between devices (e.g., vehicles, pedestrian user devices such as mobile devices, and / or other devices) and transportation infrastructure systems. In some implementations, RSUs can communicate with servers, base stations, and / or other systems that can perform centralized management functions. ™

[0037] ​In one or more examples, the one or more objects can include one or more VRUs (e.g., one or more pedestrians) or one or more other vehicles. The one or more processors of the vehicle can limit an amount of possible acceleration or speed of the vehicle based on determining the limited FOV of the driver and the one or more objects relative to the vehicle (e.g., within a threshold distance relative to the vehicle, moving relative to the vehicle, approaching the vehicle such as approaching a side and / or front of the vehicle, etc.).

[0038] In one or more examples, the one or more processors of the vehicle can determine a movement intent (e.g., an intent to drive the vehicle) of the driver based on detecting a release of a brake pedal of the vehicle, a depression of an accelerator pedal of the vehicle, and / or a shift of a transmission of the vehicle to a forward gear. The one or more processors of the vehicle can activate the FCW based on determining the movement intent of the driver. In one or more examples, the FCW can include a visual display warning, an audio warning, and / or a vibration.

[0039] In one or more aspects, during operation for disabling vehicle acceleration or speed control (e.g., when the vehicle is stopped at an intersection or other area), the one or more driver sensors of the vehicle can sense a gaze of a driver of the vehicle to produce driver sensor data. The driver sensor data including the gaze of the driver can be stored in a memory of the vehicle.

[0040] The one or more processors of the vehicle (e.g., a DMS of the vehicle) can determine a FOV of a driver of the vehicle based on the driver sensor data (e.g., based on the gaze of the driver). The one or more processors of the vehicle can compare the FOV of the driver to a predetermined threshold of FOV. The one or more processors of the vehicle can determine a non-limited FOV of the driver based on the FOV of the driver being greater than or equal to the predetermined threshold of FOV (e.g., a wide FOV, which can indicate an attentive driver). In one or more examples, the predetermined threshold of FOV can be a predetermined threshold angle of FOV of the driver or a percentage of a predetermined threshold angle of FOV of the driver. As previously noted, in some cases, a predetermined threshold can be used to determine a non-limited FOV and a limited FOV. For example, in such cases, the predetermined threshold can be a threshold number of driver gazes (or saccades) that fall within a particular FOV.

[0041] In some examples, the one or more processors of the vehicle can determine, based on the driver sensor data, that the driver’s head rotation is such that the driver is not looking at the road for a certain period of time (e.g., eyes are averted from the road) (e.g., the head is in an eyes-averted position, such as when the head is in a downward position). The one or more processors of the vehicle can compare the certain amount of time that the driver’s head is in the eyes-averted position to a predetermined threshold of the amount of time that the driver’s head is in the eyes-averted position (e.g., averted from the road). The one or more processors of the vehicle can determine (e.g., assume) that the driver has an unrestricted FOV based on the certain amount of time being less than the threshold amount of time that the driver’s head is in the eyes-averted position.

[0042] The one or more traffic sensors of the vehicle can sense the environment of the vehicle to generate traffic sensor data, and can determine, based on the traffic sensor data, that there are no objects relative to the vehicle, such as no objects within a threshold distance relative to the vehicle and / or no objects moving relative to the vehicle, or no objects are approaching the vehicle (e.g., side or front of the vehicle). The one or more processors of the vehicle can release the limit on the amount of acceleration or speed of the vehicle based on determining that the driver has an unrestricted FOV and there are no objects relative to the vehicle (e.g., no objects within a threshold distance relative to the vehicle, no objects moving relative to the vehicle, no objects are approaching the side or front of the vehicle, etc.).

[0043] Using the limited acceleration or speed provided by the systems and techniques described herein can reduce the amount of sudden movement from AEB intervention that the driver can experience. The limited acceleration or speed can allow for fewer AEB interventions, and allow for a smoother driving experience for the driver in a densely populated urban environment. Human-machine interface (HMI) communications, such as via FCW, can support the driver re-engaging in the driving task. While examples are described herein using limited acceleration, the systems and techniques described herein can be used to limit the speed or other actions of the vehicle.

[0044] Additional aspects of the disclosure are described in more detail below.

[0045] Figure 1is a perspective view of a motor vehicle having a driver monitoring system in accordance with aspects of the present disclosure. The vehicle 100 can include a forward-facing camera 112 mounted within the cab that views through the windshield 102. The vehicle can also include a cab-facing camera 114 mounted within the cab that faces the occupants of the vehicle 100 and, in particular, the driver of the vehicle 100. Although one set of mounting positions for the cameras 112 and 114 is shown with respect to the vehicle 100, other mounting locations can be used for the cameras 112 and 114. For example, one or more cameras can be mounted on one of the driver or passenger B-pillars 126 or one of the driver or passenger C-pillars 128, such as near the top of the pillar 126 or 128. As another example, one or more cameras can be mounted at the front of the vehicle 100, such as behind the radiator grill 130 or integrated with the bumper 132. As a further example, one or more cameras can be mounted as part of the driver or passenger side mirror assembly 134.

[0046] The camera 112 can be oriented such that the field of view of the camera 112 captures the scene in front of the vehicle 100 in the direction in which the vehicle 100 is moving when in drive mode or in a forward direction. In some aspects, an additional camera can be located at the rear of the vehicle 100 and oriented such that the field of view of the additional camera captures the scene behind the vehicle 100 in the direction in which the vehicle 100 is moving when in reverse mode or in a reverse direction. Although aspects of the present disclosure can be described with reference to a “forward-facing” camera (with reference to the camera 112), aspects of the present disclosure can similarly apply to a “rear-facing” camera facing in the reverse direction of the vehicle 100. Thus, benefits obtained when the vehicle 100 is traveling in the forward direction can similarly be obtained when the vehicle 100 is traveling in the reverse direction.

[0047] Further, although aspects of the present disclosure can be described with reference to a “forward-facing” camera (with reference to the camera 112), aspects of the present disclosure can similarly apply to input received from an array of cameras mounted about the vehicle 100 to provide a greater field of view that can be parallel to the ground about up to 360 degrees and / or about up to 360 degrees in a vertical direction perpendicular to the ground. For example, additional cameras can be mounted about the outside of the vehicle 100, such as on or integrated in doors, on or integrated in wheels, on or integrated in bumpers, on or integrated in a hood, and / or on or integrated in a roof.

[0048] The camera 114 can be oriented such that the field of view of the camera 114 captures the scene in the cab of the vehicle with sufficient detail and includes the user operator of the vehicle, and in particular, the face of the user operator of the vehicle to discern head rotation (e.g., a head down position) and / or gaze direction (e.g., eye looking position) of the user operator.

[0049] Each of the cameras 112 and 114 can include one, two, or more image sensors, such as including a first image sensor. When there are multiple image sensors, the first image sensor can have a larger field of view (FOV) than the second image sensor, or the first image sensor can have a different sensitivity or a different dynamic range than the second image sensor. In one example, the first image sensor can be a wide-angle image sensor, and the second image sensor can be a telephoto image sensor. In another example, the first sensor is configured to obtain images through a first lens having a first optical axis, and the second sensor is configured to obtain images through a second lens having a second optical axis different from the first optical axis. Additionally or alternatively, the first lens can have a first magnification, and the second lens can have a second magnification different from the first magnification. Such a configuration can occur in a camera module having a lens group, with multiple image sensors and associated lenses located in offset positions within the camera module. Additional image sensors having larger, smaller, or the same field of view can be included.

[0050] Each image sensor can include components 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, complementary metal-oxide-semiconductor (CMOS) sensors, and / or time-of-flight detectors. The apparatus can also include one or more components for gathering and / or focusing light rays into one or more image sensors, including simple lenses, compound lenses, spherical lenses, and aspherical lenses. These components can be controlled to capture first, second, and / or more image frames. The image frames can be processed to form a single output image frame (such as through a fusion operation), and the output image frame is further processed in accordance with aspects described herein.

[0051] As used herein, an image sensor can refer to the image sensor itself and any particular other component coupled to the image sensor for generating image frames for processing by an image signal processor or other logic circuit or storage in memory, whether a short-term buffer or long-term non-volatile storage. For example, an image sensor can include other components of a camera, including a shutter, a buffer, or other readout circuitry for accessing individual pixels of the image sensor. An image sensor can also refer to an analog front end or other circuitry for converting analog signals to a digital representation of an image frame that is provided to digital circuitry coupled to the image sensor.

[0052] Figure 2 A block diagram illustrating an example image processing configuration for a vehicle is shown in accordance with one or more aspects of the disclosure. The vehicle 100 can include or otherwise be coupled to an image signal processor 212 for processing image frames from one or more image sensors, such as a first image sensor 201, a second image sensor 202, and a depth sensor 240. In some implementations, the vehicle 100 also includes or is coupled to a processor (e.g., CPU) 204 and a memory 206 storing instructions 208. The device 100 can also include or be coupled to a display 214 and an input / output (I / O) component 216. The I / O component 216 can be used for interaction with a user, such as a touchscreen interface and / or physical buttons. The I / O component 216 can also include a network interface for communicating with other devices, such as other vehicles, a mobile device of an operator, and / or a remote monitoring system. The network interface can include one or more of a wide area network (WAN) adapter 252, a local area network (LAN) adapter 253, and / or a personal area network (PAN) adapter 254. An example WAN adapter 252 is a 4G LTE or 5G NR wireless network adapter. An example LAN adapter 253 is an IEEE 802.11 WiFi wireless network adapter. An example PAN adapter 254 is a Bluetooth wireless network adapter. Each of the adapters 252, 253, and / or 254 can be coupled to an antenna, including multiple antennas configured for main set reception and diversity reception and / or configured for receiving particular frequency bands. The vehicle 100 can also include or be coupled to a power source 218, such as a battery or alternator. The vehicle 100 can also include or be coupled to a communication bus 220, such as a controller area network (CAN) bus, a local interconnect network (LIN) bus, a media oriented system transport (MOST) bus, a time triggered Figure 2 Additional features or components not shown in FIG. 2 can be included. In one example, a wireless interface that can include one or more transceivers and associated baseband processors can be coupled to or included in the WAN adapter 252 for a wireless communication device. In another example, an analog front end (AFE) for converting analog image frame data to digital image frame data can be coupled between the image sensors 201 and 202 and the image signal processor 212.

[0053] The vehicle 100 can include a sensor hub 250 for interfacing with sensors to receive data about movement of the vehicle 100, data about the environment surrounding the vehicle 100, and / or other non-camera sensor data. One example non-camera sensor is a gyroscope, i.e., a device configured to measure rotation, orientation, and / or angular velocity to generate motion data. Another example non-camera sensor is an accelerometer, i.e., a device configured to measure acceleration, which can also be used to determine velocity and distance traveled by integrating the measured acceleration as appropriate, and one or more of the acceleration, velocity, and / or distance can be included in the generated motion data. In further examples, the non-camera sensor can be a global positioning system (GPS) receiver, a light detection and ranging (LiDAR) system, a radio detection and ranging (RADAR) system, or other ranging system. For example, the sensor hub 250 can interface to a vehicle bus for communicating configuration commands and / or receiving information from vehicle sensors 272, such as a distance (e.g., ranging) sensor or a vehicle-to-vehicle (V2V) sensor (e.g., a sensor for receiving information from nearby vehicles).

[0054] The image signal processor (ISP) 212 can receive image data such as for forming image frames. In one aspect, a local bus connection couples the image signal processor 212 to image sensors 201 and 202 of a first camera 203 that can correspond to camera 112 of Figure 1 and a second camera 205 that can correspond to camera 114 of Figure 1 In another aspect, a wire interface can couple the image signal processor 212 to an external image sensor. In a further aspect, a wireless interface can couple the image signal processor 212 to image sensors 201, 202.

[0055] The first camera 203 can include a first image sensor 201 and a corresponding first lens 231. The second camera 205 can include a second image sensor 202 and a corresponding second lens 232. Each of the lenses 231 and 232 can be controlled by an associated autofocus (AF) algorithm 233 executed in the ISP 212 that adjusts the lenses 231 and 232 to focus on a particular focal plane at a certain scene depth from the image sensors 201 and 202. The AF algorithm 233 can be aided by a depth sensor 240. In some aspects, the lenses 231 and 232 can have a fixed focal length.

[0056] The first image sensor 201 and the second image sensor 202 are configured to capture one or more image frames. The lenses 231 and 232 focus light at the image sensors 201 and 202 through one or more apertures for receiving light, one or more shutters for blocking light when outside of an exposure window, one or more color filter arrays (CFAs) for filtering light outside of a particular frequency range, one or more analog front-ends for converting analog measurements to digital information, and / or other suitable components for imaging.

[0057] In some aspects, the image signal processor 212 can execute instructions from memory, such as instructions 208 from memory 206, instructions stored in a separate memory coupled to or included in the image signal processor 212, or instructions provided by the processor 204. Additionally or alternatively, the image signal processor 212 can include specific hardware configured to perform one or more operations described in this disclosure, such as one or more integrated circuits (ICs). For example, the image signal processor 212 can include one or more image front-ends (IFE) 235, one or more image post-processing engines (IPE) 236, and one or more auto exposure compensation (AEC) 234 engines. The AF 233, AEC 234, IFE 235, IPE 236 can each include dedicated circuitry embodied as software code executed by the ISP 212 and / or a combination of hardware within the ISP 212 and software code executed on the ISP.

[0058] In some implementations, the memory 206 can include a non-transitory or non- volatile computer-readable medium storing computer-executable instructions 208 to perform all or a portion of one or more operations described in this disclosure. In some implementations, the instructions 208 include a camera application (or other suitable application) for generating images or video to be executed during operation of the vehicle 100. The instructions 208 can also include other applications or programs for the vehicle 100 to execute, such as an operating system, a mapping application, or an entertainment application. The camera application, such as executed by the processor 204, can cause the vehicle 100 to generate images using the image sensors 201 and 202 and the image signal processor 212. The memory 206 can also be accessed by the image signal processor 212 to store processed frames or by the processor 204 to obtain processed frames. In some aspects, the vehicle 100 includes a system on a chip (SoC) that combines the image signal processor 212, the processor 204, the sensor hub 250, the memory 206, and the input / output components 216 into a single package.

[0059] In some aspects, at least one of image signal processor 212 or processor 204 executes instructions to perform various operations described herein, including object detection, risk map generation, driver monitoring, and driver alerting operations. For example, execution of the instructions can instruct image signal processor 212 to begin or end capturing image frames or sequences of image frames. In some aspects, processor 204 can include one or more general purpose processor cores 204A capable of executing one or more software programs, such as instructions 208 stored within memory 206. For example, processor 204 can include one or more application processors configured to execute a camera application (or other suitable application for generating images or video) stored in memory 206.

[0060] In executing the camera application, processor 204 can be configured to instruct image signal processor 212 to perform one or more operations with reference to image sensors 201 or 202. For example, the camera application can receive a command to begin a video preview display, upon receiving the command, capture and process a video including a sequence of image frames from one or more image sensors 201 or 202, and display the video on an information display on display 114 in the cab of vehicle 100.

[0061] In some aspects, in addition to the ability to execute software to cause vehicle 100 to perform a number of functions or operations, such as the operations described herein, processor 204 can include an IC or other hardware (e.g., an artificial intelligence (AI) engine 224). In some other aspects, vehicle 100 does not include processor 204, such as when all described functionality is configured in image signal processor 212.

[0062] In some aspects, display 214 can include one or more suitable displays or screens that allow user interaction and / or present items to a user, such as a preview of image frames captured by image sensors 201 and 202. In some aspects, display 214 is a touch-sensitive display. I / O components 216 can be or include any suitable mechanism, interface, or device to receive input (such as commands) from a user and provide output to a user through display 214. For example, I / O components 216 can include (but are not limited to) a graphical user interface (GUI), a keyboard, a mouse, a microphone, a speaker, a squeezable bezel, one or more buttons (such as a power button), a slider, a switch, and the like. In some aspects involving autonomous driving, I / O components 216 can include an interface to a bus of the vehicle for providing commands and information to and receiving information from vehicle systems 270, including propulsion systems (e.g., commands to increase or decrease speed or apply brakes) and steering systems (e.g., commands to turn wheels, change a route, or change a final destination).

[0063] While shown as coupled to each other via the processor 204, the components, such as the processor 204, the memory 206, the image signal processor 212, the display 214, and the I / O components 216, can be coupled to each other via other various means, such as via one or more local buses, which are not shown for the sake of simplicity. While the image signal processor 212 is illustrated as separate from the processor 204, the image signal processor 212 can be a core of the processor 204 that is an application processor unit (APU), included in a system on a chip (SoC), or otherwise included in the processor 204. While reference is made to the vehicle 100 in examples herein in order to include aspects of the disclosure, some of the device components can not be shown in the vehicle 100 in order to prevent obscuring aspects of the disclosure. Additionally, other components, numbers of components, or combinations of components can be included in a suitable vehicle for performing aspects of the disclosure. Thus, the disclosure is not limited to a particular configuration of devices or components, including the vehicle 100. Figure 2

[0064] As previously mentioned, driver behavior such as driver distraction is a key factor in most traffic accidents. In order to avoid collisions caused by driver distraction, vehicles are typically implemented with automatic emergency braking (AEB) functionality. As previously noted, AEB is an advanced driver assistance system (ADAS) that can provide automatic braking based on sensor data to assist the driver in avoiding a collision. AEB can be equipped with forward collision warning (FCW) functionality that can be used to alert the driver of a dangerous driving situation.

[0065] AEB can be triggered in a variety of different driving scenarios. In one example driving scenario, a vehicle can be stopped at an intersection of a roadway. If the driver of the vehicle becomes distracted (e.g., by engaging in a secondary task such as looking down at their smartphone or taking their eyes off the roadway), the driver’s attention can be directed to a narrower field of view compared to if the driver were not distracted. When the driver’s attention is directed to this narrower field of view, the driver will be unable to detect an increased risk of an object (e.g., a VRU such as a pedestrian, other vehicle, etc.) relative to the vehicle (such as within a threshold distance relative to the vehicle, or approaching and / or entering the intersection). This type of driving scenario typically requires the driver or the vehicle to perform an emergency braking maneuver. When the vehicle performs AEB, the emergency brakes will engage to cause the vehicle to come to a sudden stop. This sudden stop can cause the driver to experience a sudden, jarring, jolting movement, which can reduce trust in the vehicle’s risk detection assistance systems and can significantly decrease the comfort and enjoyment of the driver’s driving experience.

[0066] Figure 3 ​An example of a vehicle parked at an intersection is shown. Specifically, Figure 3 This is a diagram 300 illustrating an example of a vehicle 310 parked at an intersection 360 of two roads 370 and 380. In one or more examples, the vehicle 310 may be... Figure 1 Similarly, vehicle 100 is equipped with sensors (e.g., cameras). For example, vehicle 310 may be equipped with... Figure 1 The camera 114 is configured to capture a scene within the driver's cab (e.g., passenger compartment) of the vehicle 310 (e.g., capture images and / or video of the scene). In one or more examples, the camera 114 within the driver's cab of the vehicle 310 may be oriented such that the field of view (FOV) of the camera 114 can capture the head and / or face of the driver (e.g., user operator) of the vehicle 310 with sufficient detail to distinguish the driver's head rotation (e.g., a position where the gaze is taken away from the intersection 360 ahead, which may be referred to as a "gaze-off" position, such as a head-down position) and / or gaze direction (e.g., direction of eye gaze).

[0067] exist Figure 3 In the area of ​​intersection 360 of roads 370 and 380, pedestrians 320a, 320b, and 320c (as examples of VRUs), other VRUs 330a and 330b (e.g., in the form of cyclists) and traffic lights 340a and 340b are shown. Figure 3 In the example, two pedestrians 320a and 320b are shown walking toward intersection 360 to cross road 380 directly in front of vehicle 310.

[0068] In one or more examples, when the driver of vehicle 310 is not distracted, the driver's FOV should be a typical wide (e.g., unrestricted) FOV of the intersection ahead 360, which FOV is... Figure 3 It is exemplified as FOV 350a. In Figure 3 In the diagram, pedestrian 320a is shown as being located within the driver's field of view (FOV) 350a. Because the driver's FOV 350a covers pedestrian 320a, the driver is informed and aware of the presence of pedestrian 320a crossing in front of the vehicle 310, and is thus able to avoid a collision with pedestrian 320a.

[0069] However, when the driver of vehicle 310 is distracted (such as looking down at an object (e.g., a mobile device, such as a cellular phone)), the driver's field of view (FOV) may be reduced or limited, such as in Figure 3 The example is FOV 350b. For example... Figure 3As shown, the pedestrian 320a is not located within the driver's FOV 350b. Since the driver's FOV 350b does not cover the pedestrian 320a, the driver is not made aware or conscious of the presence of the pedestrian 320a crossing in front of the vehicle 310. If the driver were to begin to accelerate the vehicle 310 in the presence of the pedestrian 320a, the vehicle would need to perform an AEB, which would result in the vehicle 310 coming to an abrupt stop, resulting in the driver experiencing a jolt movement. Accordingly, an improved system and technique for assisting the driver to avoid a collision while reducing the amount of jolt movement from an AEB intervention can be useful.

[0070] In one or more aspects, the system and techniques provide for vehicle acceleration control of a vehicle (e.g., intersection acceleration functionality). In one or more examples, due to detection of an object (e.g., a VRU, such as a pedestrian, other vehicle, etc.) relative to the vehicle (e.g., within a threshold distance relative to the vehicle, or approaching and / or entering an intersection, such as while the vehicle is stopped at the intersection), driver intent to move (e.g., evidenced by release of the brake or depression of the gas pedal), and determination of driver distraction (e.g., due to reduced or limited driver field of view), the vehicle acceleration control can be enabled without braking.

[0071] In one or more examples, when an object (e.g., a VRU, other vehicle, etc.) relative to the vehicle (e.g., within a threshold distance relative to the vehicle, approaching and / or entering an intersection, etc.) is detected while the vehicle is at rest (e.g., at an intersection), a limited acceleration (e.g., limiting the possible maximum acceleration) can be implemented for the vehicle. In one or more examples, the driver can be notified (e.g., via FCW) of the object relative to the vehicle (e.g., within a threshold distance relative to the vehicle, approaching the vehicle and / or moving relative to the vehicle). When the driver is no longer distracted (e.g., the driver is looking in many directions) and thus the driver's field of view is restored, the acceleration limit can be removed.

[0072] Figure 4 Examples of different allowable vehicle accelerations (e.g., full acceleration or limited acceleration) for different driver FOVs are shown. Specifically, Figure 4 is a diagram illustrating an example scenario 400 with drivers 420a, 420b having different FOVs 430a, 430b. In this example, the driver 420a has a full FOV 430a, while the driver 420b has a limited FOV 430b. In this example, the driver 420a is able to see the object 410 (e.g., a pedestrian, other vehicle, etc.) relative to the vehicle 410 (e.g., within a threshold distance relative to the vehicle, approaching the vehicle and / or moving relative to the vehicle). In this example, the driver 420b is not able to see the object 410 relative to the vehicle 410 (e.g., within a threshold distance relative to the vehicle, approaching the vehicle and / or moving relative to the vehicle) due to the limited FOV 430b. Figure 4In the example scenario 400, two scenarios 410a, 410b are included. In scenario 410a, a driver 420a is operating a vehicle (not shown) that is stopped at an intersection (not shown). The driver 420a is waiting to drive the vehicle in a direction indicated by arrow 470a (indicating a direction of travel). A VRU 440a (e.g., in the form of a bicyclist) is shown to be traveling such that the VRU 440a is crossing the intersection in front of the vehicle of the driver 420a.

[0073] In Figure 4 In scenario 410a, the driver 420a is shown with a typical wide (e.g., unimpaired) FOV 430a having an angle 480a. Since the FOV 430a of the driver 420a is shown to cover the VRU 440a, the driver 420a is informed and aware of the presence of the VRU 440a crossing in front of the vehicle of the driver 420a, and thus, the driver 420a can avoid a collision with the VRU 440a. Since the driver 420a has an unimpaired FOV 430a, it can be assumed that the driver 420a is attentive 450a, and the acceleration of the vehicle need not be limited (e.g., full acceleration 460a of the vehicle is available).

[0074] In scenario 410b, a driver 420b is operating a vehicle (not shown) that is stopped at an intersection (not shown). The driver 420b is waiting to drive the vehicle in a direction indicated by arrow 470b. A VRU 440b in the form of a bicyclist is traveling such that the VRU 440b is crossing the intersection in front of the vehicle of the driver 420b.

[0075] In scenario 410b, the driver 420b is shown with an impaired FOV 430b (also referred to as a reduced FOV) having an angle 480b. The angle 480b of the impaired FOV 430b is less than the angle 480a of the unimpaired FOV 430a. The FOV 430b of the driver 420b is shown to not cover the VRU 440b, and thus, the driver 420b is not aware of the presence of the VRU 440b crossing in front of the vehicle of the driver 420b. Since the driver 420b has an impaired FOV 430b, it can be assumed that the driver 420b is distracted 450b (e.g., the driver is looking down at his smartphone). To avoid the possibility of performing AEB, the acceleration of the vehicle can be limited (e.g., full acceleration is not available), and the driver 420b can be warned 460b of the presence of the VRU 440b (e.g., via FCW).

[0076] In one or more examples, using limited acceleration reduces the amount of sudden, jerky movement that a driver may experience from AEB intervention. Limited acceleration allows for less AEB intervention and a smoother driving experience in densely populated urban environments. Human-machine interface (HMI) communications, such as via FCW, can support the driver's re-engagement with driving tasks.

[0077] Figure 5 and Figure 6 Examples of the procedures for enabling and disabling the acceleration function are shown respectively. Specifically, Figure 5 This is a flowchart illustrating an example of a detailed process 500 for enabling the acceleration function.

[0078] In one or more examples, in the context of enabling acceleration functionality Figure 5 During the operation of process 500, at box 505, one or more processors of the vehicle (e.g., Figure 9 The processor 910 can determine that the vehicle (e.g., a car) is stationary, such as parked at an intersection or other area (e.g., a parking lot, a driveway, etc.). One or more driver sensors of the vehicle can sense the driver's gaze (and / or head rotation, such as a head-down position) to generate driver sensor data. In one or more examples, one or more driver sensors may be mounted in the passenger compartment of the vehicle and may include a camera (e.g., such as...) Figure 1 (Camera 114). At frame 510, driver sensor data, including the driver's gaze (and / or head rotation), may be stored (e.g., recorded) in the vehicle's memory.

[0079] In one or more examples, one or more processors of the vehicle may determine whether the driver's FOV is restricted (e.g., reduced or restricted FOV) based on analysis of the driver's FOV or analysis of driver sensor data, which may indicate whether the driver is attentive or distracted (e.g., interacting with objects, such as operating a mobile device).

[0080] In one or more examples, one or more processors of a vehicle (e.g., a driver monitoring system (DMS)) can determine a FOV of a driver of the vehicle based on driver sensor data (e.g., based on a gaze of the driver). The one or more processors of the vehicle can compare the determined FOV of the driver to a predetermined threshold for the FOV of the driver. The one or more processors of the vehicle can determine a reduced or limited FOV of the driver (e.g., a narrow FOV, which can indicate a distracted driver) based on the FOV of the driver being less than the predetermined threshold for the FOV. In one or more examples, the predetermined threshold for the FOV can be a predetermined threshold angle for the FOV of the driver (e.g., 90 degrees) or a percentage of a predetermined threshold angle for the FOV of the driver (e.g., 80 percent).

[0081] In some cases, a predetermined threshold can be used to determine a non-limited FOV and a limited FOV. For example, the predetermined threshold can be a threshold number of driver gazes (or saccades) that fall within a particular FOV (e.g., within a particular time period such as ten seconds, thirty seconds, one minute, etc.). In such an example, if the driver performs a number of gazes (or saccades) within the particular FOV that is greater than the threshold number of driver gazes, the one or more processors can assign the particular FOV to the driver. If the one or more processors determine that the user performs a number of gazes (or saccades) within the full FOV that is below the threshold, the one or more processors can determine that the user has a limited FOV. Referring to Figure 4 As an illustrative example, the one or more processors can determine that the number of driver gazes outside of the limited FOV 430b is less than the threshold number of driver gazes, and in response, can determine that the FOV of the driver is limited (e.g., limited to the limited FOV 430b). In some examples, if the number of driver gazes outside of the limited FOV 430 becomes greater than the threshold number of driver gazes, the one or more processors can determine that the FOV of the user has returned to the non-limited FOV 430a.

[0082] In some examples, the one or more processors of the vehicle can determine (e.g., assume) a reduced or limited FOV of the driver based on the head pose and eye gaze of the driver. For example, the one or more processors of the vehicle can determine, based on the driver sensor data, that the head of the driver is rotated such that the driver is not looking at (e.g., has taken their eyes off of) the road for a period of time (e.g., the head of the driver is in an “eyes off” position, such as when the head of the driver is in a downward position). In such examples, the gaze of the driver is narrowed and the head pose of the driver is oriented away from a forward position (e.g., looking down instead of forward through the windshield), indicating a limited FOV. The one or more processors of the vehicle can compare the period of time that the driver is not looking at the road (e.g., is in the eyes off position) to a predetermined threshold amount of time (e.g., the driver has their eyes off of the road). The one or more processors of the vehicle can determine (e.g., assume) a reduced or limited FOV of the driver based on the amount of time being greater than or equal to the threshold amount of time that the head of the driver is in the eyes off position. At block 510, the one or more processors can determine that the driver has a reduced or limited FOV (e.g., a narrowed gaze).

[0083] In one or more examples, one or more traffic sensors of the vehicle (e.g., mounted on or integrated within the vehicle) can sense an environment of the vehicle to produce traffic sensor data. In some examples, the one or more traffic sensors can include a camera, a radar sensor, an infrared sensor, and / or a LiDAR sensor. The one or more processors of the vehicle can detect, based on the traffic sensor data, one or more objects relative to the vehicle, such as one or more objects within a threshold distance relative to the vehicle, moving relative to the vehicle, and / or approaching the vehicle (e.g., approaching a side and / or front of the vehicle). In one or more examples, the one or more objects can include one or more VRUs (e.g., one or more pedestrians), one or more other vehicles, and / or other objects. At block 520, the one or more processors of the vehicle can detect one or more objects relative to the vehicle, such as one or more objects approaching the vehicle (e.g., a potential threat from the side of the vehicle, such as a person).

[0084] At block 525, the one or more processors of the vehicle can enable an acceleration function based on determining that the driver has a reduced or limited FOV and detecting one or more objects relative to the vehicle (e.g., relative to the vehicle moving, within a threshold distance relative to the vehicle, and / or approaching the vehicle (e.g., approaching a side and / or front of the vehicle)). At block 530, the one or more processors of the vehicle can limit an amount of possible acceleration of the vehicle based on enabling the acceleration function.

[0085] In one or more examples, at block 535, the one or more processors of the vehicle can detect a release of a brake pedal by the driver of the vehicle. At block 540, the one or more processors of the vehicle can detect a light press of an accelerator pedal by the driver of the vehicle. At block 545, the one or more processors of the vehicle can detect a shift of a gear of a transmission of the vehicle to a drive (D) by the driver of the vehicle.

[0086] In one or more examples, the one or more processors of the vehicle can determine a movement intent (e.g., an intent to drive the vehicle) of the driver based on detecting the release of the brake pedal of the vehicle, the press of the accelerator pedal of the vehicle, and / or the shift of the transmission of the vehicle to the drive. At block 550, the one or more processors of the vehicle can determine that the driver has a movement intent based on detecting the release of the brake pedal of the vehicle, detecting the press of the accelerator pedal of the vehicle, and / or detecting the shift of the transmission of the vehicle to the drive.

[0087] At block 555, the one or more processors of the vehicle can activate an FCW (e.g., display a textual explanation warning, which can include a direction to avoid a collision) based on determining the movement intent of the driver. In one or more examples, the FCW can include a visual display warning (e.g., a color warning light and / or a textual warning), an audio warning (e.g., an audio sound and / or a warning message), and / or a vibration (e.g., a seat and / or steering wheel vibration) to attract the attention of the driver.

[0088] Figure 6 is a flowchart illustrating an example of a detailed procedure 600 for disabling an acceleration function. In one or more examples, during the procedure 600 for disabling an acceleration function of Figure 6 During the operation of the procedure 600 of Figure 9the processor 910) can determine that the vehicle (e.g., a car) is stationary, such as stopped at an intersection or other area (e.g., a parking lot, a driveway, etc.). One or more driver sensors of the vehicle can sense a gaze (and / or a head rotation, such as a lowered head position) of a driver of the vehicle to obtain driver sensor data. The one or more driver sensors can be installed in a cab (e.g., a passenger compartment) of the vehicle, and can include a camera (e.g., the camera 114) of the vehicle. At block 620, the driver sensor data including the gaze (and / or the head rotation) of the driver can be stored (e.g., logged) into a memory of the vehicle. Figure 1

[0089] In one or more examples, the one or more processors of the vehicle can determine whether a FOV of the driver is unrestricted (e.g., an unrestricted FOV) based on analyzing the FOV of the driver or analyzing the driver sensor data, which can indicate whether the driver is attentive or distracted.

[0090] In one or more examples, the DMS of the vehicle can determine a FOV of a driver of the vehicle based on the driver sensor data (e.g., based on the gaze of the driver). The one or more processors of the vehicle can compare the determined FOV of the driver to a predetermined threshold for the FOV of the driver. The one or more processors of the vehicle can determine an unrestricted FOV of the driver based on the FOV of the driver being greater than or equal to the predetermined threshold for the FOV (e.g., a typical wide FOV, which can indicate an attentive driver). In one or more examples, the predetermined threshold for the FOV can be a predetermined threshold angle for the FOV of the driver or a percentage of a predetermined threshold angle for the FOV of the driver.

[0091] In some examples, the one or more processors of the vehicle can determine that a head rotation of the driver is such that the driver is not looking at the road (e.g., has eyes off the road) for a certain period of time (e.g., the head of the driver is in an “eyes off position”). The one or more processors of the vehicle can compare the certain period of time that the head of the driver is in the eyes off position to a predetermined threshold amount of time that the head of the driver is in the eyes off position. The one or more processors of the vehicle can determine an unrestricted FOV of the driver based on the certain amount of time being less than the threshold amount of time that the head of the driver is in the eyes off position. At block 630, the one or more processors can determine that the driver has an unrestricted FOV (e.g., is not in a narrow gaze).

[0092] ​In some examples, one or more traffic sensors of the vehicle that are mountable on or integrated in the vehicle can sense an environment of the vehicle to obtain traffic sensor data. In one or more examples, the one or more traffic sensors can include a camera, a radar sensor, an infrared sensor, and / or a LiDAR sensor. One or more processors of the vehicle can (or can not) detect, based on the traffic sensor data, an object relative to the vehicle (e.g., an object that is within a threshold distance relative to the vehicle, that is moving relative to the vehicle, and / or that is approaching the vehicle (such as approaching a side and / or front of the vehicle)). In one or more examples, the one or more objects can include one or more VRUs (e.g., one or more pedestrians), one or more other vehicles, and / or other objects. At block 640, the one or more processors of the vehicle can detect that there is no object relative to the vehicle (e.g., no potential threat is detected), such as no object that is within a threshold distance relative to the vehicle, that is moving relative to the vehicle, that is approaching the vehicle, etc.

[0093] At block 650, the one or more processors of the vehicle can disable the acceleration function based on determining that the driver has an unrestricted FOV and that there is no object relative to the vehicle. At block 660, the one or more processors of the vehicle can allow a full amount of possible acceleration of the vehicle based on disabling the acceleration function.

[0094] Figure 7 is a flowchart illustrating an example of a process 700 for enabling an acceleration function. The process 700 can be performed by a device or by a component of the device, a system, or an apparatus (e.g., a chipset of the device, one or more processors of the device, or other component or system of the device). The device can be a vehicle (e.g., Figure 1 the vehicle 100 of FIG. 1, or Figure 3 the vehicle 310 of FIG. 3), can be part of or within a vehicle, or be other device. The operations of the process 700 can be implemented as software components that are executed and run on one or more processors of the device (e.g., Figure 9 the processor 910 of FIG. 9, or other processors). Further, transmission and reception of signals by the device in the process 700 can be enabled, for example, by one or more antennas and / or one or more transceivers (e.g., wireless transceivers) of the device.

[0095] At block 710, the device (or a component thereof) can determine a field of view (FOV) of a driver of the vehicle based on the driver sensor data (e.g., FOV 430a). In some cases, the device (or a component thereof) can determine the FOV of the driver based on a predetermined number of gazes of the driver within the FOV. For example, as previously described, the device (or a component thereof) can assign the FOV to the driver if the driver performs a number of gazes (or saccades) within the FOV that is greater than a threshold number of gazes of the driver.

[0096] At block 720, the device (or a component thereof) can determine that the FOV of the driver is limited based on a FOV threshold. For example, as previously noted, the predetermined threshold for the FOV can include a predetermined threshold angle of the FOV of the driver or a percentage of a predetermined threshold angle of the FOV of the driver. In some cases, the device (or a component thereof) can compare the FOV of the driver to the predetermined threshold for the FOV of the driver and can determine that the FOV of the driver is limited based on the FOV of the driver being less than the FOV threshold. In some examples, as previously described, the predetermined threshold can be a threshold number of gazes (or saccades) of the driver. For example, if the device (or a component thereof) determines that the user performs a number of gazes (or saccades) within the FOV that is below a threshold number of gazes of the driver (e.g., which can indicate that the driver saccades too little or not at all to the sides of the full FOV), the device (or a component thereof) can determine that the user has a limited FOV.

[0097] In some cases, to determine that the FOV of the driver is limited, the device (or a component thereof) can determine, based on the driver sensor data, that the head of the driver is rotated for a period of time to be in a position that takes the gaze away from a road on which the vehicle is traveling. The device (or a component thereof) can compare the period of time to a predetermined threshold amount of time for the head of the driver to take the gaze away from the road. The device (or a component thereof) can determine that the FOV of the driver is limited based on the period of time being greater than or equal to the predetermined threshold amount of time.

[0098] At block 730, the device (or a component thereof) can detect one or more objects relative to the vehicle based on the traffic sensor data. For example, the device (or a component thereof) can determine that the one or more objects are within a threshold distance relative to the vehicle (and / or moving relative to the vehicle and / or approaching the vehicle such as approaching a side and / or front of the vehicle). In one illustrative example, the device (or a component thereof) can determine that a pedestrian is moving relative to the vehicle and that the distance between the pedestrian and the vehicle is decreasing as the pedestrian moves. The one or more objects can include a vulnerable road user (VRU) (e.g., one or more pedestrians) or one or more other vehicles.

[0099] At block 740, the device (or a component thereof) can control an amount of possible acceleration (or speed) of the vehicle based on determining the reduced FOV of the driver and detecting the one or more objects within the threshold distance relative to the vehicle. For example, the device (or a component thereof) can constrain the amount of acceleration allowed for the vehicle to be no (zero) acceleration or a maximum acceleration that is less than a normal operating acceleration of the vehicle (e.g., 1 g acceleration) (e.g., 0.1 g acceleration).

[0100] In some aspects, the device (or a component thereof) can determine the movement intent of the driver based on detecting a release of a brake pedal of the vehicle, a depression of an accelerator pedal of the vehicle, a shift of a transmission of the vehicle to a forward gear, or other action indicative of a movement intent of the driver. In some cases, the device (or a component thereof) can activate a forward collision warning (FCW) based on determining the movement intent of the driver. In some examples, the FCW includes a visual display warning, an audio warning, a vibration, and / or other output. The FCW can be output to a display of the vehicle and / or a device of a driver or passenger of the vehicle (e.g., an extended reality (XR) device such as an augmented reality (AR) or mixed reality (MR) device, a mobile device, or other device).

[0101] In some cases, the device (or a component thereof) can obtain driver sensor data using one or more driver sensors of the vehicle. For example, the device (or a component thereof) can use a driver sensor of the vehicle to sense a driver of the vehicle to obtain the driver sensor data. In some cases, the driver sensor can include or be part of an occupant sensing system and / or a driver monitoring system. The driver sensor can include any type of sensor such as one or more cameras, infrared sensors, radar sensors, LIDAR sensors, any combination thereof, and / or other sensors. In some examples, the device (or a component thereof) can obtain traffic sensor data using one or more traffic sensors of the vehicle that are directed to an environment of the vehicle. Additionally or alternatively, in some cases, the device (or a component thereof) can obtain traffic sensor data from at least one of another vehicle or a roadside unit (RSU) (e.g., via one or more V2X or DSRC messages).

[0102] Figure 8 FIG. 8 is a flowchart illustrating an example of a process 800 for disabling an acceleration function. The process 800 can be performed by a device or by a component, system, or apparatus of the device (e.g., a chipset of the device, one or more processors of the device, or other component or system of the device). The device can be a vehicle (e.g., a vehicle 100 of Figure 1 FIG. 1 or a vehicle 100 of Figure 3a vehicle 310), is part of a vehicle or within a vehicle, or is other equipment. The operations of process 800 can be implemented as software components executed and run on a processor 910 of the device (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), an application-specific processor, a microprocessor, or other processors) or other processor of the device. Further, the transmission and reception of signals by the device in process 800 can be enabled, for example, by one or more antennas and / or one or more transceivers (e.g., wireless transceivers) of the device. Figure 9

[0103] At block 810, the device (or a component thereof) can determine, based on the driver sensor data, an unrestricted field of view (FOV) of a driver of the vehicle.

[0104] At block 820, the device (or a component thereof) can determine, based on the traffic sensor data, that there are no objects relative to the vehicle.

[0105] At block 830, the device (or a component thereof) can release a restriction on an amount of possible acceleration of the vehicle based on determining the unrestricted FOV of the driver and that there are no objects relative to the vehicle.

[0106] In some examples, a device can include various components, such as one or more input devices, one or more output devices, one or more processors, one or more microprocessors, one or more microcomputers, one or more cameras, one or more sensors, and / or other components configured to perform the steps of the processes described herein. In some examples, a device can include a display, one or more network interfaces configured to communicate and / or receive data, any combination thereof, and / or other components. The one or more network interfaces can be configured to communicate and / or receive wired and / or wireless data, including data according to 3G, 4G, 5G, and / or other cellular standards, data according to WiFi (802.1 lx) standards, data according to Bluetooth ™ standards, data according to Internet Protocol (IP) standards, and / or other types of data.

[0107] Components of a device can be implemented in circuitry. For example, a component can include or be implemented using electronic circuitry or other electronic hardware, which can include one or more programmable electronic circuits (e.g., microprocessors, graphics processing units (GPUs), digital signal processors (DSPs), central processing units (CPUs), and / or other suitable electronic circuits), and / or can include or be implemented using computer software, firmware, or any combination thereof, for performing various operations described herein.

[0108] ​The processes 700 and 800 are each illustrated as a logical flow diagram, the operation of which represents a sequence of operations that can be implemented in hardware, computer instructions, or a combination thereof. In the context of computer instructions, the operations represent computer-executable instructions stored, for example, on one or more computer-readable storage media that, when executed by one or more processors, perform the recited operations. Generally, computer-executable instructions include routines, programs, objects, components, data structures, and the like that perform particular functions or implement particular data types. The order in which the operations are described is not intended to be construed as a limitation, and any number of the described operations can be combined in any order and / or in parallel to implement the processes.

[0109] Additionally, the processes 700, 800, and / or other processes described herein can be performed under the control of one or more computer systems configured with executable instructions, and can be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) executing collectively on one or more processing units, by hardware or combinations thereof. As noted above, the code can be stored on a computer-readable or machine-readable storage medium, such as a computer program product. The computer-readable or machine-readable storage medium can be non-transitory.

[0110] Figure 9 is a block diagram illustrating an example of a computing system 900 that can be used for spatiotemporal cooperative learning by the disclosed system for multi-sensor fusion. Specifically, Figure 9 An example of a computing system 900 is illustrated, which can be, for example, any computing device that makes up an internal computing system, a remote computing system, a camera, or any component thereof, where the components of the system communicate with each other using connections 905. The connections 905 can be physical connections using a bus, or direct connections into the processor 910, such as in a chipset architecture. The connections 905 can also be virtual connections, networking connections, or logical connections.

[0111] In some aspects, the computing system 900 is a distributed system, where the functionality described by the present disclosure can be distributed within a data center, multiple data centers, a peer-to-peer network, and the like. In some aspects, one or more of the described system components represent many such components each performing some or all of the functionality the component is described to perform. In some aspects, the components can be physical or virtual devices.

[0112] The example system 900 includes at least one processing unit (CPU or processor) 910 and a connection 905 that communicatively couples various system components including the system memory 915, such as read-only memory (ROM) 920 and random-access memory (RAM) 925, to the processor 910. The computing system 900 can include a cache of high-speed memory 1212 directly coupled to, in close proximity to, or integrated as part of the processor 910.

[0113] The processor 910 can include any general purpose processor and a hardware service or software service, such as services 932, 934, and 936 stored in storage device 930, configured to control the processor 910 as well as a specific purpose processor where software instructions are incorporated into the actual processor design. The processor 910 can essentially be a completely self-contained computing system, containing multiple cores or processors, a bus, memory controller, and cache, etc. Multi-core processing systems can be symmetric or asymmetric.

[0114] To enable user interaction, the computing system 900 includes an input device 945, which can represent any number of input mechanisms, such as a microphone for speech, a touch-sensitive screen for gesture or graphical input, keyboard, mouse, motion input, speech and the like. The computing system 900 can also include output device(s) 935, which can be one or more of a number of output mechanisms known to those of skill in the art. In some instances, multi-modal systems can enable a user to provide multiple types of input to communicate with the computing system 900.

[0115] The computing system 900 can include communications interface 940 that can generally govern and manage the user input and system output. The communications interface can receive and / or send wired or wireless communications using wired and / or wireless transceivers, including utilizing audio jacks / plugs, microphone jacks / plugs, Universal Serial Bus (USB) ports / plugs, Apple ™ Lightning ™ ports / plugs, Ethernet ports / plugs, fiber optic ports / plugs, dedicated wired ports / plugs, 3G, 4G, 5G, and / or other cellular data network wireless signal transfers, Bluetooth ™ wireless signal transfers, Bluetooth ™ Low Energy (BLE) wireless signal transfers, IBEACON ™wireless signal transmissions of radio frequency identification (RFID), near field communication (NFC), dedicated short-range communications (DSRC), 802.11 Wi-Fi, wireless local area network (WLAN), visible light communication (VLC), worldwide interoperability for microwave access (WiMAX), infrared (IR) communication, public switched telephone network (PSTN) signal transmission, integrated services digital network (ISDN) signal transmission, ad hoc network signal transmission, radio wave signal transmission, microwave signal transmission, infrared signal transmission, visible light signal transmission, ultraviolet light signal transmission, wireless signal transmission along the electromagnetic spectrum, or some combination thereof.

[0116] The communication interface 940 can also include one or more ranging sensors (e.g., LIDAR sensors, laser rangefinders, RF radar, ultrasonic sensors, and infrared (IR) sensors) configured to collect data and provide measurements to the processor 910, whereby the processor 910 can be configured to perform determinations and calculations needed to obtain various measurements of the one or more ranging sensors. In some examples, the measurements can include time of flight, wavelength, azimuth angle, elevation angle, distance, linear velocity, and / or angular velocity, or any combination thereof. The communication interface 940 can also include one or more global navigation satellite system (GNSS) receivers or transceivers for determining a location of the computing system 900 based on one or more signals received from one or more satellites associated with one or more GNSS systems. GNSS systems include, but are not limited to, GPS in the United States, Global Navigation Satellite System (GLONASS) in Russia, BeiDou Navigation Satellite System (BDS) in China, and Galileo GNSS in Europe. There is no limitation as to operation on any particular hardware arrangement, and thus the underlying features herein can be readily substituted for improved hardware or firmware arrangements as they are developed.

[0117] The storage device 930 can be a nonvolatile and / or non-transitory and / or computer-readable memory device and can be a hard disk or other type of computer readable medium that can store data which can be accessed by a computer, such as a magnetic hard disk, flash memory card, solid state memory device, digital tape, random access memory (RAM), any other memory, or a combination of memories. The storage device 930 can be configured to store data, including, for example, instructions and / or other data. In some examples, the storage device 930 can be a non-transitory computer-readable storage medium.® a card, a smart card chip, an EMV chip, a subscriber identity module (SIM) card, a mini / micro / nano / pico SIM card, another integrated circuit (IC) chip / card, a random access memory (RAM), a static RAM (SRAM), a dynamic RAM (DRAM), a read only memory (ROM), a programmable read only memory (PROM), an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), a flash EPROM (FLASH EPROM), a cache memory (e.g., a level 1 (LI) cache, a level 2 (L2) cache, a level 3 (L3) cache, a level 4 (L4) cache, a level 5 (L5) cache, other (L#) cache), a resistive random access memory (RRAM / ReRAM), a phase change memory (PCM), a spin transfer torque RAM (STT-RAM), another memory chip or cartridge, and / or combinations thereof.

[0118] The storage device 930 can include software services, servers, services, and the like that, when code defining such software is executed by the processor 910, cause the system to perform a function. In some aspects, a hardware service that performs a particular function can include the software components stored in a computer-readable medium that are necessary to perform the function. The term “computer-readable medium” includes, but is not limited to, portable or fixed storage devices, optical storage devices, and various other mediums capable of storing, containing or carrying instruction and / or data. A computer-readable medium can include a non-transitory medium in which data can be stored and which does not include carrier waves and / or transitory electronic signals propagating wirelessly or over wired connections. Examples of a non-transitory medium can include, but are not limited to, a magnetic disk or tape, optical storage media such as compact disk (CD) or digital versatile disk (DVD), flash memory, memories, or memory devices. A computer-readable medium can have stored thereon code and / or machine-executable instructions that can represent a procedure, function, subprogram, program, routine, subroutine, module, software package, class, or any combination of instructions, data structures, or program statements. A code segment can be coupled to another code segment or a hardware circuit by passing and / or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. can be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, etc.

[0119] In the descriptions above, specific details are set forth in order to provide a thorough understanding of various aspects and examples provided herein. However, persons having ordinary skill in the art will recognize that the application, which is described herein with specificity, can be practiced with or without the details that have been set forth and with modifications not specifically described herein. In other instances, well known methods, procedures, components and networks have not been described in detail so as not to unnecessarily obscure aspects of the application. Although illustrative aspects and examples of the present application have been described in detail herein, with reference to the above descriptions, it is to be understood that the application is not limited to the aspects and examples described herein, but is applicable to any aspects or equivalents thereof. Accordingly, various features and aspects of the above-described application can be used individually or jointly. Further, the application can be utilized in any number of environments and applications beyond the specific examples described herein, without departing from the broader spirit and scope of the present specification. Accordingly, the specification and drawings are to be regarded as illustrative in nature and not as restrictive. The description and drawings are to be regarded as illustrative in nature and not as restrictive. For the purposes of exemplification, the methods are described in a particular order. It should be appreciated that in alternate aspects, the methods can be performed in an order other than that described.

[0120] For the sake of explanation, in some instances the techniques can be presented with reference to specific electrical circuit configurations and diagrams. The device, components in the circuit, the process, and other aspects can be implemented with or without employing any or all of these specific circuit configurations. The circuit diagrams used herein are not intended to be exhaustive or to limit the various aspects to the particular forms disclosed. Other well-known components or structures can be used instead of, or in addition to, the components and structures described here. For instance, the circuit, system, network, process, and other components can be shown as blocks in the diagrams to avoid obscuring the aspects in unnecessary detail.

[0121] Furthermore, those skilled in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the aspects disclosed herein can 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 can 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.

[0122] Various aspects can be described herein in terms of processes and operations performed or implemented by functional blocks, circuitry, modules, or the like. Although specific circuitry can be described herein as performing a process or operation, such electrical circuitry is an example of means for performing the process or operation. That is, the specification can be read to describe specific examples of means for performing processes or operations in accordance with aspects of the disclosure. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components. In some embodiments, the various circuit elements and components can be implemented or performed with one or more hardware components and / or software components.

[0123] The processes and methods described above according to the examples can be implemented using stored computer-executable instructions or computer-executable instructions acquired (e.g., downloaded) in other ways from computer-readable media. Such instructions can comprise, for example, instructions and data which cause or otherwise configure a general purpose computer, special purpose computer, or a processing device to perform a certain function or group of functions. Portions of computer resources used can be accessible via a network. The computer executable instructions can be, for example, binaries, intermediate format instructions such as assembly language, firmware, source code, etc. Examples of computer-readable media that can be used to store instructions, information used by the examples, and / or information created during methods according to the described examples include magnetic or optical disks, flash memory, USB devices provided with non-volatile memory, network storage, and the like.

[0124] In some aspects, computer-readable storage devices, media and memory can include cables or wireless signals containing bitstreams and the like. However, non-transitory computer-readable storage media expressly exclude media such as energy, carrier signals, electromagnetic waves, and signals per se when mentioned.

[0125] Those skilled in the art will appreciate that information and signals can be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that can be referenced throughout the above description can be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof consistent with the state of the art.

[0126] The various illustrative logical blocks, modules, and circuits described in connection with the aspects disclosed herein can be implemented or performed with a hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof and can be embodied in any of a number of various forms. When implemented in software, firmware, middleware, or microcode, the program code or code segments (e.g., computer program products) that accomplish the necessary tasks can be stored in a computer-readable or machine-readable medium. A processor(s) can perform the necessary tasks. Examples of the various shapes include: a laptop computer, a smart phone, a mobile phone, a tablet device, or other small form factor personal computers, personal digital assistants, rack-mounted devices, stand-alone devices, etc. The functionality described herein can also be embodied in peripheral devices or add-in cards. By way of further example, such functionality can also be implemented by way of a circuit on a different chip or in different processes executed by a single chip.

[0127] Instructions, media for conveying such instructions, computing resources for executing them, and other structures for supporting such computing resources are example components for providing the functionality described in the present disclosure.

[0128] The techniques described herein can be implemented in electronic hardware, computer software, firmware, or any combination thereof. Such techniques can be implemented in any of various devices such as a general purpose computer, a wireless communication device handset, or an integrated circuit device having many uses including application in wireless communication device handsets and other devices. Any features described as modules or components can be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques can be realized at least in part by a computer-readable data storage medium comprising program code including instructions that, when executed, performs one or more of the methods, algorithms and / or operations described above. The computer-readable data storage medium can form part of a computer program product, which can include packaging materials. The computer-readable medium can comprise memory or data storage media, such as random access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, magnetic or optical data storage media, and the like. Additionally or in the alternative, the techniques can be realized at least in part by a computer-readable communication medium that carries or communicates program code in the form of instructions or data structures and that can be accessed, read, and / or executed by a computer, such as a propagated signal or wave.

[0129] The program code can be executed by a processor, which can include one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application-specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Such a processor can be configured to perform any of the techniques described in this disclosure. A general purpose processor can be a microprocessor; but in the alternative, the processor can be any conventional processor, controller, microcontroller, or state machine. A processor can also be implemented as a combination of computing devices, e.g., 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. Accordingly, the term “processor,” as used herein can refer to any of the foregoing structure, any combination of the foregoing structure, or any other structure or apparatus suitable for implementation of the techniques described herein.

[0130] Those of ordinary skill in the art will appreciate that the less than (“<”) and greater than (“>”) symbols or terms used herein can be replaced with less than or equal to (“ ”) and greater than or equal to (“ ”) symbols, respectively, without departing from the scope of this description.

[0131] Where components are described as being "configured to" perform certain operations, such configuration can be accomplished, for example, by designing electronic circuitry or other hardware to perform the operation, by programming programmable electronic circuitry (e.g., microprocessor or other suitable electronic circuitry) to perform the operation, or any combination thereof.

[0132] The phrases "coupled to" or "communicatively coupled to" mean that any component is either directly or indirectly physically connected to another component, and / or any component is either directly or indirectly in communication with another component (e.g., connected to the other component through a wired or wireless connection and / or other suitable communication interface).

[0133] Claim language or other language reciting "at least one of a set or collection of items" and / or "one or more of a set or collection of items" indicates that a member of the set or a member of the collection can be included in, but not limited to, only one instance of the set or collection, any single instance of the set or collection, multiple instances of the set or collection, any combination of instances of the set or collection, and / or the like. For example, a recitation of "at least one of A and B" or "at least one of A or B" can mean A, B, or A and B. In another example, a recitation of "at least one of A, B, and C" or "at least one of A, B, or C" can mean A, B, C, A and B, A and C, B and C, A and B and C, or any other ordering of A, B, and C, with or without repetition, and / or the like. Language reciting "at least one of a set or collection of items" and / or "one or more of a set or collection of items" does not limit the set to the items listed. For example, a recitation of "at least one of A and B" or "at least one of A or B" can mean A, B, or A and B, and can additionally include items not listed in the set of A and B. The phrases "at least one" and "one or more" are used interchangeably herein.

[0134] Claim language or other language reciting "at least one processor configured to," "at least one processor configured to," "one or more processors configured to," "one or more processors configured to," and the like indicates that a single processor or multiple processors (in any combination) can perform the associated operations. For example, claim language recitation "at least one processor configured to: X, Y, and Z" means a single processor can be used to perform operations X, Y, and Z; or multiple processors each tasked with a specific subset of operations X, Y, and Z, such that the multiple processors together perform X, Y, and Z; or a group of multiple processors working together to perform operations X, Y, and Z. In another example, claim language recitation "at least one processor configured to: X, Y, and Z" can mean any single processor can perform only at least a subset of operations X, Y, and Z.

[0135] Where reference is made to one or more elements performing one or more functions, one element can perform the functions, or more than one element can perform the functions collectively. Where reference is made to one or more elements being configured to cause another element (e.g., a device) to perform a function, one element can be configured to cause the other element to perform all of the functions, or more than one element can be collectively configured to cause the other element to perform the functions.

[0136] Where reference is made to an entity (e.g., any entity or device described herein) performing or being configured to perform a function (e.g., a step of a method), the entity can be configured to cause one or more elements (either individually or collectively) to perform the function. The one or more components of the entity can include at least one memory, at least one processor, at least one communication interface, another component configured to perform one or more (or all) of the functions, and / or any combination thereof. Where reference is made to an entity performing a function, the entity can be configured to cause one component to perform all of the functions, or more than one component collectively to perform the functions. Where the entity is configured to cause more than one component to collectively perform the functions, each function can not need to be performed by each component of those components (e.g., different functions can be performed by different components), and / or each function can not need to be performed collectively only by one component (e.g., different components can perform different sub-functions of the function).

[0137] The various illustrative logical blocks, modules, engines, circuits, and algorithm steps described in connection with the aspects disclosed herein can be implemented as electronic hardware, computer software, firmware, or combinations thereof. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, engines, 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 can 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 application.

[0138] The techniques described herein can also be implemented in electronic hardware, computer software, firmware, or any combination thereof. Such techniques can be implemented in any of various devices such as a general purpose computer, a wireless communication device handset, or an integrated circuit device having many uses including application in wireless communication device handsets and other devices. Any features described as engines, modules, or components can be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques can be realized at least in part by a computer-readable data storage medium or media having computer code thereon for causing a processor to implement one or more of the methods described above. The computer-readable data storage medium or media can form part of a computer program product. The computer-readable medium or media can include memory or data storage media, such as random access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, magnetic or optical data storage media, and the like. Additionally or in the alternative, the techniques can be realized at least in part by a computer-readable communication medium that carries or communicates program code in the form of instructions or data structures and that can be accessed, read, and / or executed by a computer, such as a propagated signal or wave.

[0139] The program code can be executed by a processor, which can include one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application-specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Such a processor can be configured to perform any of the techniques described in this disclosure. A general-purpose processor can be a microprocessor; but in the alternative, the processor can be any conventional processor, controller, microcontroller, or state machine. A processor can also be implemented as a combination of computing devices, e.g., 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. Accordingly, the term “processor,” as used herein can refer to any of the foregoing structure, any combination of the foregoing structure, or any other structure or apparatus suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein can be provided within dedicated software modules or hardware modules configured for encoding and decoding, or incorporated in a combined video encoder-decoder (CODEC).

[0140] Illustrative aspects of the present disclosure include: Aspect 1. A method for enabling vehicle acceleration control, the method comprising: determining, by one or more processors of a vehicle and based on driver sensor data, a field of view (FOV) of a driver of the vehicle; determining, by the one or more processors, based on a FOV threshold, that the FOV of the driver is limited, wherein the FOV threshold is one of a predetermined threshold angle of the FOV of the driver or a percentage of the predetermined threshold angle of the FOV of the driver; detecting, by the one or more processors of the vehicle and based on traffic sensor data, one or more objects within a threshold distance relative to the vehicle; and controlling, by the one or more processors of the vehicle, an amount of possible acceleration or speed of the vehicle based on determining that the FOV of the driver is limited and detecting the one or more objects within the threshold distance.

[0141] Aspect 2. The method of aspect 1, wherein determining, by the one or more processors, that the FOV of the driver is limited comprises: determining, by the one or more processors, based on the driver sensor data, that a head of the driver rotated into a position to look away from a road on which the vehicle is traveling for a period of time; comparing, by the one or more processors, the period of time to a predetermined threshold amount of time for the head of the driver to look away from the road; and determining, by the one or more processors, that the FOV of the driver is limited based on the period of time being greater than or equal to the predetermined threshold amount of time.

[0142] Aspect 3. The method of any one of aspects 1 or 2, further comprising: determining, by the one or more processors of the vehicle, a movement intent of the driver based on detecting at least one of: a release of a brake pedal of the vehicle, a depression of an accelerator pedal of the vehicle, or a shift of a transmission of the vehicle to a forward gear.

[0143] Aspect 4. The method of aspect 3, further comprising: activating, by the one or more processors of the vehicle, a forward collision warning (FCW) based on determining the movement intent of the driver.

[0144] Aspect 5. The method of aspect 4, wherein the FCW comprises at least one of a visual display warning, an audio warning, or a vibration.

[0145] Aspect 6. The method of any one of aspects 1-5, wherein the one or more objects comprise at least one of one or more vulnerable road users (VRUs) or one or more other vehicles.

[0146] Aspect 7. The method of any one of aspects 1-6, further comprising: sensing, by one or more driver sensors of the vehicle, the driver of the vehicle to obtain the driver sensor data.

[0147] Aspect 8. The method of any one of aspects 1-7, further comprising: sensing, by one or more traffic sensors of the vehicle, an environment of the vehicle to obtain the traffic sensor data.

[0148] Aspect 9. The method of any one of aspects 1-8, further comprising: obtaining the traffic sensor data from at least one of another vehicle or a roadside unit (RSU).

[0149] Aspect 10. The method of any one of aspects 1-9, further comprising: determining that the FOV of the driver is limited based on the FOV of the driver being less than the FOV threshold.

[0150] Aspect 11. The method of any one of aspects 1 or 10, wherein the one or more objects are detected to be approaching the vehicle.

[0151] Aspect 12. The method of any one of aspects 1-11, wherein the FOV of the driver is determined based on a predetermined number of gazes of the driver within the FOV.

[0152] Aspect 13. An apparatus for enabling vehicle acceleration control of a vehicle, the apparatus comprising: at least one memory; and at least one processor coupled to the at least one memory and configured to: determine a field of view (FOV) of a driver of the vehicle based on driver sensor data; determine that the FOV of the driver is limited based on a FOV threshold, wherein the FOV threshold is one of a predetermined threshold angle of the FOV of the driver or a percentage of the predetermined threshold angle of the FOV of the driver; detect one or more objects within a threshold distance relative to the vehicle based on traffic sensor data; and control an amount of possible acceleration or speed of the vehicle based on determining that the FOV of the driver is limited and detecting the one or more objects within the threshold distance.

[0153] Aspect 14. The device of aspect 13, wherein to determine that the FOV of the driver is limited, the at least one processor is configured to: determine, based on the driver sensor data, that a head of the driver rotated into a position to look away from a road on which the vehicle is traveling for a period of time; compare the period of time to a predetermined threshold amount of time for the head of the driver to look away from the road; and determine that the FOV of the driver is restricted based on the period of time being greater than or equal to the predetermined threshold amount of time.

[0154] Aspect 15. The device of any one of aspects 13 or 14, wherein the at least one processor is configured to determine a movement intent of the driver based on detecting at least one of: a release of a brake pedal of the vehicle, a depression of an accelerator pedal of the vehicle, or a shift of a transmission of the vehicle to a forward gear.

[0155] Aspect 16. The device of aspect 15, wherein the at least one processor is configured to activate a forward collision warning (FCW) based on determining the movement intent of the driver.

[0156] Aspect 17. The device of aspect 16, wherein the FCW comprises at least one of a visual display warning, an audio warning, or a vibration.

[0157] Aspect 18. The device of any one of aspects 13 to 17, wherein the one or more objects comprise at least one of one or more vulnerable road users (VRUs) or one or more other vehicles.

[0158] Aspect 19. The device of any one of aspects 13 to 18, wherein the at least one processor is configured to obtain the driver sensor data using one or more driver sensors of the vehicle.

[0159] Aspect 20. The device of any one of aspects 13 to 19, wherein the at least one processor is configured to obtain the traffic sensor data using one or more traffic sensors of the vehicle that are directed to an environment of the vehicle.

[0160] Aspect 21. The device of any one of aspects 13 to 20, wherein the at least one processor is configured to obtain the traffic sensor data from at least one of another vehicle or a roadside unit (RSU).

[0161] Aspect 22. The apparatus of any one of aspects 13 to 21, wherein the at least one processor is configured to determine the FOV of the driver based on a predetermined number of fixations of the driver within the FOV.

[0162] Aspect 23. The apparatus of any one of aspects 13 to 22, wherein the at least one processor is configured to determine that the FOV of the driver is limited based on the FOV of the driver being less than the FOV threshold.

[0163] Aspect 24. The apparatus of any one of aspects 13 to 23, the one or more objects are detected to be approaching the vehicle.

[0164] Aspect 25. The apparatus of any one of aspects 13 to 24, wherein the apparatus is part of the vehicle.

[0165] Aspect 26. The apparatus of any one of aspects 13 to 25, wherein the apparatus is the vehicle.

[0166] Aspect 27. A non-transitory computer-readable storage medium of a vehicle, the non-transitory computer-readable storage medium including instructions stored thereon that, when executed by at least one processor, cause the at least one processor to perform operations in accordance with any of aspects 1 to 12.

[0167] Aspect 28. An apparatus, the apparatus comprising: one or more means for performing the operations of any of aspects 1 to 12.

[0168] Aspect 29. A method for disabling vehicle acceleration control, the method comprising: determining, by one or more processors of a vehicle, an unrestricted field of view (FOV) of a driver of the vehicle based on driver sensor data; determining, by the one or more processors of the vehicle, an absence of objects relative to the vehicle based on traffic sensor data; and releasing, by the one or more processors of the vehicle, a limit on an amount of possible acceleration of the vehicle based on determining the unrestricted FOV of the driver and the absence of objects relative to the vehicle.

[0169] Aspect 30. An apparatus for disabling vehicle acceleration control of a vehicle, the apparatus comprising: at least one memory; and at least one processor coupled to the at least one memory and configured to: determine an unrestricted field of view (FOV) of a driver of the vehicle based on driver sensor data; determine no objects relative to the vehicle based on traffic sensor data; and release a restriction on an amount of possible acceleration of the vehicle based on determining the unrestricted FOV of the driver and no objects relative to the vehicle.

[0170] Aspect 31. A non-transitory computer-readable storage medium of a vehicle, the non-transitory computer-readable storage medium comprising instructions stored thereon that, when executed by at least one processor, cause the at least one processor to perform operations of Aspect 29.

[0171] Aspect 32. An apparatus, the apparatus comprising: one or more means for performing the operations of Aspect 29.

[0172] The preceding description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but is to be accorded the full scope consistent with the language claims, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.”

Claims

1. A method for enabling vehicle acceleration control, the method comprising: The driver's field of view (FOV) of the vehicle is determined by one or more processors of the vehicle and based on driver sensor data. The one or more processors determine that the driver's FOV is limited based on a FOV threshold, wherein the FOV threshold is one of a predetermined threshold angle of the driver's FOV or a percentage of the predetermined threshold angle of the driver's FOV; The one or more processors of the vehicle and based on traffic sensor data detect one or more objects within a threshold distance relative to the vehicle. as well as The one or more processors of the vehicle control the possible amount of acceleration or speed of the vehicle based on determining that the driver's FOV is limited and detecting the one or more objects within the threshold distance.

2. The method of claim 1, wherein determining by the one or more processors that the driver's FOV is limited includes: The one or more processors determine, based on the driver sensor data, that the driver's head has rotated to a position that removes his gaze from the road over which the vehicle is traveling; The one or more processors compare the time period with a predetermined threshold amount of time during which the driver's head takes its gaze away from the road; as well as The one or more processors determine that the driver's FOV is limited based on the time period being greater than or equal to the predetermined threshold time.

3. The method according to claim 1, further comprising: The driver's intention to move is determined by one or more processors of the vehicle based on detecting at least one of the following: release of the brake pedal of the vehicle, depressing of the accelerator pedal of the vehicle, or shifting of the vehicle's transmission into a forward gear.

4. The method according to claim 3, further comprising: The forward collision warning (FCW) is activated by one or more processors of the vehicle based on determining the driver's intention to move.

5. The method of claim 4, wherein the FCW includes at least one of a visual display warning, an audio warning, or a vibration warning.

6. The method of claim 1, wherein the one or more objects include at least one or more vulnerable road users (VRUs) or one or more other vehicles.

7. The method according to claim 1, further comprising: The driver of the vehicle is sensed by one or more driver sensors of the vehicle to obtain driver sensor data.

8. The method according to claim 1, further comprising: The environment of the vehicle is sensed by one or more traffic sensors of the vehicle to obtain the traffic sensor data.

9. The method according to claim 1, further comprising: The traffic sensor data is obtained from at least one of another vehicle or roadside unit (RSU).

10. The method according to claim 1, further comprising: The driver's FOV is determined to be limited based on the fact that the driver's FOV is less than the FOV threshold.

11. The method of claim 1, wherein one or more objects are detected approaching the vehicle.

12. The method of claim 1, wherein the driver's FOV is determined based on a predetermined number of gazes of the driver within the FOV.

13. A device for activating vehicle acceleration control, the device comprising: At least one memory; and At least one processor, the at least one processor being coupled to the at least one memory and being configured to: The driver's field of view (FOV) of the vehicle is determined based on driver sensor data. The driver's FOV is determined to be limited based on a FOV threshold, wherein the FOV threshold is either a predetermined threshold angle of the driver's FOV or a percentage of the predetermined threshold angle of the driver's FOV. Detect one or more objects within a threshold distance relative to the vehicle based on traffic sensor data; as well as The possible acceleration or speed of the vehicle is controlled based on determining that the driver's field of view (FOV) is limited and detecting one or more objects within the threshold distance.

14. The apparatus of claim 13, wherein, in order to determine that the driver's FOV is limited, the at least one processor is configured to: Based on the driver sensor data, it is determined that the driver's head has rotated to a position that removes his gaze from the road over which the vehicle is traveling; The time period is compared with a predetermined threshold amount of time during which the driver takes his / her head away from the road; as well as The driver's field of view (FOV) is determined to be limited based on the time period being greater than or equal to the predetermined threshold time.

15. The apparatus of claim 13, wherein the at least one processor is configured to determine the driver’s intention to move based on detecting at least one of the following: release of the brake pedal of the vehicle, depressing of the accelerator pedal of the vehicle, or shifting of the vehicle’s transmission into a forward gear.

16. The apparatus of claim 15, wherein the at least one processor is configured to activate a forward collision warning (FCW) based on determining the driver's intention to move.

17. The apparatus of claim 16, wherein the FCW includes at least one of a visual display warning, an audio warning, or a vibration warning.

18. The apparatus of claim 13, wherein the one or more objects include at least one or more vulnerable road users (VRUs) or one or more other vehicles.

19. The apparatus of claim 13, wherein the at least one processor is configured to use one or more driver sensors of the vehicle to obtain the driver sensor data.

20. The apparatus of claim 13, wherein the at least one processor is configured to acquire traffic sensor data using one or more traffic sensors of the vehicle pointing toward the environment of the vehicle.

21. The apparatus of claim 13, wherein the at least one processor is configured to obtain the traffic sensor data from at least one of another vehicle or roadside unit (RSU).

22. The apparatus of claim 13, wherein the at least one processor is configured to determine the driver's FOV based on a predetermined number of gazes made by the driver within the FOV.

23. The apparatus of claim 13, wherein the at least one processor is configured to determine that the driver's FOV is limited based on the driver's FOV being less than the FOV threshold.

24. The apparatus of claim 13, wherein the one or more objects are detected to be approaching the vehicle.

25. The apparatus of claim 13, wherein the apparatus is part of the vehicle.

26. The apparatus of claim 13, wherein the apparatus is the means of transport.

27. A non-transitory computer-readable storage medium for a vehicle, the non-transitory computer-readable storage medium comprising instructions stored thereon, the instructions causing the at least one processor, when executed by at least one processor, to: The driver's field of view (FOV) of the vehicle is determined based on driver sensor data. The driver's FOV is determined to be limited based on a FOV threshold, wherein the FOV threshold is either a predetermined threshold angle of the driver's FOV or a percentage of the predetermined threshold angle of the driver's FOV. Detect one or more objects within a threshold distance relative to the vehicle based on traffic sensor data; as well as The possible acceleration or speed of the vehicle is controlled based on determining that the driver's field of view (FOV) is limited and detecting one or more objects within the threshold distance.

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