The present application generally relates to a monitoring system for determining driver readiness for takeover of vehicle control from an autonomous driving system
A monitoring system for determining driver readiness for takeover vehicle control from an autonomous driving system is provided. The monitoring system comprises a driver monitoring system that includes at least one driver monitoring sensor configured to capture an attribute of the driver indicative of driver ability to take over vehicle control. The monitoring system also comprises an evaluation processor configured to access driver data from the driver monitoring system and to determine driver ability to take over vehicle control using the driver data from the driver monitoring system.
A method for determining driver readiness for takeover vehicle control from an autonomous driving system is also provided. The method comprises: capturing, by at least one driver monitoring sensor, an attribute of the driver indicative of driver ability to take over vehicle control; generating, by a driver monitoring system, driver data using sensor data from the at least one driver monitoring sensor; and determining, by an evaluation processor, driver ability to take over vehicle control using the driver data from the driver monitoring system.
Further objects, features, and advantages of this application will become readily apparent to persons skilled in the art after a review of the following description, with reference to the drawings and claims that are appended to and form a part of this specification.
Level 2 and 3 semi-autonomous vehicles cannot drive in all conditions and scenarios and in certain circumstances require a driver takeover control of the vehicle. No current technology in the market addresses whether the driver is ready to take over and how to re-engage the driver sufficiently. The disclosed system determines if the driver is prepared and ready to take over based on inputs such as driver gaze, impairment, cognitive load, etc. A secondary confirmation could include a constantly changing system of tasks that the driver would be asked to perform to confirm that they are “back in the loop” and paying attention.
In some embodiments, one or more of the cameras 142 are positioned such that the driver is in a field of view of the camera.
The one or more cameras 142 may be used to analyze gestures by the occupants or determine the positon and/or orientation of the occupant, or monitor indications of the occupant such as facial features indicative of emotion or condition. The biosensors 144 may include touch sensors for example, to determine if the driver is touching a certain control such as the steering wheel or gear shift. The biosensors 144 could include a heart rate monitor to determine the heart rate of the passenger, as well as, other biological indications such as temperature or skin moisture. In addition, other sensors 146 may be used such as presence, absence or position sensors to determine for example, if the occupant is wearing a safety belt, a weight sensor to determine the weight of the occupant. The driver monitor 112 may use the occupant monitoring data from the occupant monitoring sensor systems to determine the driver profile and/or baseline.
The driver monitor 112 may also be in communication with a driver communication and alert system 118. The driver communication and alert system 118 may include video screens 132, audio system 134, as well as other indicators 136. The screen may be a screen in the console and may be part of the instrument cluster, or a part of a vehicle infotainment system. The audio may be integrated into the vehicle infotainment system or a separate audio feature for example, as part of the navigation or telecommunication systems. The audio may provide noises such as beeps, chirps or chimes or may provide language prompts for example, asking questions or providing statements in an automated or pre-recorded voice. The driver communication and alert system 118 may also include other indicators for example, lamps or LEDs to provide a visual indication or stimulation either on the instrument cluster or elsewhere in the vehicle including for example, on the side view mirrors or rear view mirror.
The driver monitor 112 may also be in communication with an autonomous driving system 150. The autonomous driving system 150 may utilize the driver profile and driver baseline information for making various decisions for example, when and how to provide vehicle control handoff, when making decisions about drivers and objects (e.g. people, vehicles, etc.) around the current vehicle. In one example, a vehicle-to-vehicle communication system may provide information about a driver in a nearby car based on the driver information system and the autonomous driving system 150 may make driving decisions based on the driver profile and/or driver baseline of drivers in surrounding vehicles.
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The vehicle 200 may also include biosensors 218. The biosensor 218 may for example, be integrated into a steering wheel of the vehicle. However, other implementations may include integration into seats and/or a seatbelt or within other vehicle controls such as the gear shift or other control knobs. Biosensor 218 may determine a heartbeat, temperature, and/or moisture of the skin of the driver of the vehicle. As such, the condition of the driver may be evaluated by measuring various biosensor readings as provided by the biosensor 218. The system may also have one or more inward or cabin facing cameras 220. The cabin facing cameras 220 may include cameras that operate in the white light spectrum, infrared spectrum, or other available wavelengths. The cameras may be used to determine various gestures of the driver, position or orientation of the driver, or facial expressions of the driver to provide information about the condition of the driver (e.g. emotional state, engagement, drowsiness and impairment of the driver). Further, bioanalysis may be applied to the images from the camera to determine the condition of the driver or if the driver has experienced some symptoms of some medical state. For example, if the driver's eyes are dilated, this may be indicative of a potential medical condition which could be taken into account in controlling the vehicle. As, such, condition of the driver may be determined based on a combination of measurements from one or more sensors. For example, a heart rate in a certain range, a particular facial expression, and skin coloring within a certain range may correspond to a particular emotional state, engagement, drowsiness and/or impairment of the driver.
Cameras 222 may be used to view the external road conditions, such as in front of, behind, or to the side of the vehicle. This may be used to determine the path of the road in front of the vehicle, the lane indications on the road, the condition of the road with regard to road surface, or with regard to the environment external to the vehicle including whether the vehicle is in a rain or snow environment, as well as, lighting conditions external to the vehicle including whether there is glare or glint from the sun or other objects surrounding the vehicle as well as the lack of light due to poor road lighting infrastructure. As discussed previously, the vehicle may include rearward or sideward looking implementations of any of the previously mentioned sensors. As such, a side view mirror sensor 224 may be attached to the side view mirror of the vehicle and may include a radar, Lidar and/or camera sensor for determining external conditions relative to the vehicle including the position of objects such as other vehicles around the instant vehicle. Additionally, rearward facing camera 226 and ultrasonic sensor 228 in the rear bumper of the vehicle provide other exemplary implementations of rearward facing sensors that parallel the functionality of the forward facing sensors described previously.
The vehicle may also include an evaluation processor 230 configured to access driver data from the driver monitoring system and to determine driver ability to take over vehicle control using the driver data from the driver monitoring system. For example, the evaluation processor 230 may be in functional communication with the sensor processer 210. In some embodiments, the evaluation processor 230 may be a stand-alone unit. In some other embodiments, the evaluation processor 230 may be implemented integrally with one or more other processors, such as sensor processer 210.
With regard to
A method for determining driver readiness for takeover vehicle control from an autonomous driving system is also provided. The method includes capturing, by at least one driver monitoring sensor, an attribute of the driver indicative of driver ability to take over vehicle control. The attribute indicative of the driver ability to take over vehicle control may include, for example, cognitive load, driver engagement, driver drowsiness, driver impairment, driver tasks, and/or a gaze direction that the driver is looking.
The method also includes generating, by a driver monitoring system, driver data using sensor data from the at least one driver monitoring sensor. The driver monitor data may include, for example, computed values regarding one or more attributes indicative of driver ability to take over vehicle control.
The method proceeds with determining, by an evaluation processor, driver ability to take over vehicle control using the driver data from the driver monitoring system. This step may include, for example comparing the driver monitor data against one or more predetermined benchmark values or conditions that correspond to the driver being ready and able to take over vehicle control.
The method may also include the steps of: prompting the driver to perform an affirmative confirmation of readiness in response to a takeover request from the autonomous driving system; and determining performance of the affirmative confirmation of readiness using the driver data from the driver monitoring system. This step may include recognizing a gesture or a verbal response by the driver. Alternatively or additionally, this step may include determining performance of an action by the driver using a user interface, such as a button press or a particular interaction with a touchpad or a touch screen. This step of determining performance of the affirmative confirmation may be performed by the evaluation processor. In some embodiments, this step of determining performance of the affirmative confirmation may be performed by another system or controller, such as an infotainment system in cases where the affirmative confirmation requires interaction with the infotainment system.
The methods, devices, processing, and logic described above may be implemented in many different ways and in many different combinations of hardware and software. For example, all or parts of the implementations may be circuitry that includes an instruction processor, such as a Central Processing Unit (CPU), microcontroller, or a microprocessor; an Application Specific Integrated Circuit (ASIC), Programmable Logic Device (PLD), or Field Programmable Gate Array (FPGA); or circuitry that includes discrete logic or other circuit components, including analog circuit components, digital circuit components or both; or any combination thereof. The circuitry may include discrete interconnected hardware components and/or may be combined on a single integrated circuit die, distributed among multiple integrated circuit dies, or implemented in a Multiple Chip Module (MCM) of multiple integrated circuit dies in a common package, as examples.
The circuitry may further include or access instructions for execution by the circuitry. The instructions may be stored in a tangible storage medium that is other than a transitory signal, such as a flash memory, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM); or on a magnetic or optical disc, such as a Compact Disc Read Only Memory (CDROM), Hard Disk Drive (HDD), or other magnetic or optical disk; or in or on another machine-readable medium. A product, such as a computer program product, may include a storage medium and instructions stored in or on the medium, and the instructions when executed by the circuitry in a device may cause the device to implement any of the processing described above or illustrated in the drawings.
The implementations may be distributed as circuitry among multiple system components, such as among multiple processors and memories, optionally including multiple distributed processing systems. Parameters, databases, and other data structures may be separately stored and managed, may be incorporated into a single memory or database, may be logically and physically organized in many different ways, and may be implemented in many different ways, including as data structures such as linked lists, hash tables, arrays, records, objects, or implicit storage mechanisms. Programs may be parts (e.g., subroutines) of a single program, separate programs, distributed across several memories and processors, or implemented in many different ways, such as in a library, such as a shared library (e.g., a Dynamic Link Library (DLL)). The DLL, for example, may store instructions that perform any of the processing described above or illustrated in the drawings, when executed by the circuitry.
As a person skilled in the art will readily appreciate, the above description is meant as an illustration of the principles of this application. This description is not intended to limit the scope or application of the claim in that the assembly is susceptible to modification, variation and change, without departing from spirit of this application, as defined in the following claims.
The present application claims the benefit of the filing date of U.S. Provisional Application No. 62/863,128, filed Jun. 18, 2019, the disclosure of which is hereby incorporated herein by reference in its entirety. BACKGROUND
Filing Document | Filing Date | Country | Kind |
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PCT/US2020/038364 | 6/18/2020 | WO |
Number | Date | Country | |
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62863128 | Jun 2019 | US |