Abstract: A driver monitor system and method of optimizing use of cognitive resources of a user in a vehicle is disclosed. The system includes in-cabin video cameras, a display device, and processing circuitry. The method performed by the processing circuitry includes monitoring eye gaze direction using images from the in-cabin video cameras, gradually softening image regions and lines displayed in the display device that are outside a first vision area of the user of the vehicle, and using the eye gaze direction to predict whether the user is transitioning into a new focus vision area that had been outside the first vision area. When the user's eyes begin to move, begin sharpening softened image regions and lines such that by the time eyes have shifted into the new focus vision area, the image regions and lines in the new focus vision area reach full sharpness.

Abstract: An apparatus includes processing circuitry configured to determine an actual driving performance of a driver in a manual driving mode and a projected driving performance if the vehicle had been operated in an autonomous driving mode, compare the driving performance in the manual driving mode and the autonomous driving mode, and transmit a feedback to the driver based on the comparison. The processing circuitry can be further configured to determine a driver state of the driver in the manual driving mode, determine environmental driving condition of the vehicle, and establish a baseline behavior of the driver as a function of the driver state and the environmental driving condition.

Abstract: A method, system and non-transitory computer readable medium which monitor a road user in order to move the external position of the vehicle intent notification (eHMI) to another external position that can be seen by the road user based on the gaze direction of the road user. In some aspects, the eHMI notification displays the vehicle intent for a single autonomous vehicle. In another aspect, a group eHMI notification displays the trajectories for a plurality of autonomous and non-autonomous vehicles. Based on the gaze direction of the road user, the eHMI notification can be displayed on a single external position or on multiple external positions. Different eHMI notifications can be displayed at different external positions on the autonomous vehicle to provide information to more than one road user.

Abstract: A feedback server includes a processing circuitry configured to determine an actual driving performance of a driver in a manual driving mode and a projected driving performance if the vehicle had been operated in an autonomous driving mode, compare the driving performance in the manual driving mode and the autonomous driving mode, and transmit a feedback to the driver based on the comparison. The processing circuitry can be further configured to determine a driver state of the driver in the manual driving mode, determine environmental driving condition of the vehicle, and establish a baseline behavior of the driver as a function of the driver state and the environmental driving condition.

Abstract: A method, system and non-transitory computer readable medium for suppressing autonomous vehicle external human machine interface (eHMI) notifications to prevent confusion or distraction of a road user. The suppression conditions are based on situations where the eHMI notification is redundant, not necessary, can be simplified or should be modified due to weather or light intensity. The eHMI notifications can be suppressed on selected displays and enhanced on others. The eHMI notifications can include text and icons, flashing lights, color or light patterns, which can be modified or suppressed based on the determination that the eHMI notification will confuse or distract the road user. At a four-way stop intersection, the eHMI notification can be suppressed until the autonomous vehicle has the right-of-way. The autonomous vehicle can form a mesh network with connected vehicles at the intersection and broadcast a group eHMI while requesting that the connected vehicles suppress their eHMIs.

Abstract: A system and a method for adjusting a yielding space of a platoon are provided. The system can include camera modules, sensors, interface circuitry, processing circuitry, and memory. The sensors can detect one or more behaviors of one or more vehicles adjacent to the platoon. The processing circuitry can determine one or more triggering events between the one or more vehicles and the platoon based on the one or more behaviors. The processing circuitry can adjust the yielding space of the platoon.

Abstract: Systems and methods for alerting a pedestrian of the density of automated vehicles to non-automated vehicles in an area by broadcasting a visual signal representing a group mode status of automated vehicles travelling towards or within a roadway intersection. The group mode status may be broadcast as a percentage of automated vehicles to total vehicles or can be broadcast as a ratio of automated vehicles to non-automated vehicles on an external mode indicator of a subject automated vehicle. The visual signal may be broadcast as a pattern of lighting, a change in light intensity, a change in colors or a change in text. The group mode status may also be broadcast to a pedestrian equipped with a wireless device via vehicle-to-infrastructure communications. The group status may also be broadcast to and displayed on infrastructure component, such as a street light, display post, crosswalk sign, or building display configured to receive signals.

Abstract: A driver monitor method and system for mitigating cognitive tunneling in a vehicle includes in-cabin video cameras, a heart rate monitor, an audio-visual device, and processing circuitry that detects eye gaze direction, eye lid position, and head position using images from the in-cabin video cameras, and measures heart rate variability using the heart rate monitor. A machine learning device uses the eye gaze direction, eye lid position, head position, and heart rate variability to predict whether a driver is transitioning into a cognitive tunneling state or a fatigue state. The audio-visual device outputs one audio-visual cue to mitigate the cognitive tunneling state and outputs a different cue to mitigate the fatigue state. The machine learning device learns by performing a reinforcement learning algorithm in which the audio-video device outputs a verification request and receives a response to the verification request that is fed back to the machine learning device.

Abstract: System, methods, and other embodiments described herein relate to addressing inconsistencies between a trajectory plan and a communication from an occupant of an autonomously operated vehicle. A method of resolving inconsistent communication includes obtaining a trajectory plan for the vehicle, detecting, using one or more internal sensors, body language of the occupant, analyzing sensor data from the one or more internal sensors to determine a verbal or non-verbal communication indication by the occupant, and detecting an inconsistency between the verbal or non-verbal communication indication and the trajectory plan and: 1) modifying the trajectory plan to form a modified trajectory plan aligned with the verbal or non-verbal communication indication, or 2) transmitting a notification to the occupant prompting the occupant to adjust the verbal or non-verbal communication indication.

Abstract: A system and a method for adjusting a yielding space of a platoon are provided. The system can include camera modules, sensors, interface circuitry, processing circuitry, and memory. The sensors can detect one or more behaviors of one or more vehicles adjacent to the platoon. The processing circuitry can determine one or more triggering events between the one or more vehicles and the platoon based on the one or more behaviors. The processing circuitry can adjust the yielding space of the platoon.

Abstract: A system and method for a host vehicle to assess risk for road users is disclosed. The host vehicle monitors its surrounding driving environment and sends alerts to road users if a threat is detected. The host vehicle can determine the best course of action to mitigate a threat, and coordinate such action. The host vehicle comprises processing circuitry configured to perform the foregoing tasks. Further, the host vehicle may use a machine learning-based system comprising a trained neural network.

Abstract: Systems and methods for alerting a pedestrian of the density of automated vehicles to non-automated vehicles in an area by broadcasting a visual signal representing a group mode status of automated vehicles travelling towards or within a roadway intersection. The group mode status may be broadcast as a percentage of automated vehicles to total vehicles or can be broadcast as a ratio of automated vehicles to non-automated vehicles on an external mode indicator of a subject automated vehicle. The visual signal may be broadcast as a pattern of lighting, a change in light intensity, a change in colors or a change in text. The group mode status may also be broadcast to a pedestrian equipped with a wireless device via vehicle-to-infrastructure communications. The group status may also be broadcast to and displayed on infrastructure component, such as a street light, display post, crosswalk sign, or building display configured to receive signals.

Abstract: A driver monitor system and method of optimizing use of cognitive resources of a user in a vehicle is disclosed. The system includes in-cabin video cameras, a display device, and processing circuitry. The method performed by the processing circuitry includes monitoring eye gaze direction using images from the in-cabin video cameras, gradually softening image regions and lines displayed in the display device that are outside a first vision area of the user of the vehicle, and using the eye gaze direction to predict whether the user is transitioning into a new focus vision area that had been outside the first vision area. When the user's eyes begin to move, begin sharpening softened image regions and lines such that by the time eyes have shifted into the new focus vision area, the image regions and lines in the new focus vision area reach full sharpness.

Abstract: A driver monitor method and system for mitigating cognitive tunneling in a vehicle includes in-cabin video cameras, a heart rate monitor, an audio-visual device, and processing circuitry that detects eye gaze direction, eye lid position, and head position using images from the in-cabin video cameras, and measures heart rate variability using the heart rate monitor. A machine learning device uses the eye gaze direction, eye lid position, head position, and heart rate variability to predict whether a driver is transitioning into a cognitive tunneling state or a fatigue state. The audio-visual device outputs one audio-visual cue to mitigate the cognitive tunneling state and outputs a different cue to mitigate the fatigue state. The machine learning device learns by performing a reinforcement learning algorithm in which the audio-video device outputs a verification request and receives a response to the verification request that is fed back to the machine learning device.

Abstract: A system and a method for adjusting a lead time of external audible signals of a vehicle are provided. The system can include vehicle sensors, road user sensors, interface circuitry, processing circuitry, and memory. The road user sensors can detect one or more factors of one or more road users adjacent to the vehicle. The vehicle sensors can detect one or more conditions of the vehicle. The processing circuitry can determine a visual perception time of the one or more road users for a state change of the vehicle based on the one or more factors and the one or more conditions. The processing circuitry can adjust the lead time of the external audible signals based at least in part on the visual perception time.

Abstract: A system and a method for adjusting a yielding space of a platoon are provided. The system can include camera modules, sensors, interface circuitry, processing circuitry, and memory. The sensors can detect one or more behaviors of one or more vehicles adjacent to the platoon. The processing circuitry can determine one or more triggering events between the one or more vehicles and the platoon based on the one or more behaviors. The processing circuitry can adjust the yielding space of the platoon.

Abstract: System, methods, and other embodiments described herein relate to improving lane centering performance of an operator of a vehicle after transitioning from an automated mode of operation to a manual mode of operation. In one embodiment, a method includes, in response to detecting a transition to the manual mode of operation, modifying a sensitivity level of a lane positioning system from a first value to a second value to induce finer path following by the operator. The method includes controlling the lane positioning system according to the sensitivity level. The method also includes resetting the sensitivity level to the first value upon determining that a deviation score satisfies a stability threshold. The deviation score characterizes deviations of the vehicle from a centerline resulting from operator control inputs.

Abstract: A system and method of temperature optimization in a passenger vehicle when transporting perishable items, includes a passenger vehicle having predetermined storage compartments, an in-vehicle computer network connected to a plurality of sensors; and a display device in communication with the in-vehicle computer network. The display device obtains information about perishable items. The display device is configured to estimate time that the perishable items may be maintained in the vehicle. The conditions for perishable items may be optimized by determining parking locations and movement of the vehicle between parking locations in order to minimize temperature fluctuations in the vehicle. The display device is configured to update the user on the status of the perishable items and changed parking locations.

Abstract: A system and method of temperature optimization in a passenger vehicle when transporting perishable items, includes a passenger vehicle having predetermined storage compartments, an in-vehicle computer network connected to a plurality of sensors; and a display device in communication with the in-vehicle computer network. The display device obtains information about perishable items. The display device is configured to estimate time that the perishable items may be maintained in the vehicle. The conditions for perishable items may be optimized by determining parking locations and movement of the vehicle between parking locations in order to minimize temperature fluctuations in the vehicle. The display device is configured to update the user on the status of the perishable items and changed parking locations.

Abstract: System, methods, and other embodiments described herein relate to improving visual scanning behavior of an operator in a vehicle with a vehicle display. In one embodiment, a method includes, in response to detecting a transition to a manual mode of operating the vehicle, identifying, using at least one sensor of the vehicle, objects in a present operating environment around the vehicle according to a visual profile of the operator. The method also includes controlling the vehicle display to selectively render one or more graphic elements according to at least a gaze score.