Safety enhanced computer assisted driving method and apparatus
First Claim
1. An apparatus for computer-assisted driving, comprising:
- a communication interface to receive, from a wearable device worn by a driver of a vehicle, a current level of stress or drowsiness of the driver, wherein the wearable device includes a first multilayer neural network to locally determine the current level of stress or drowsiness of the driver, based at least in part on physiological data of the driver collected in real time by the wearable device worn by the driver;
a second multilayer neural network implemented with a hardware accelerator in the vehicle and coupled with the communication interface to locally determine a classification for behavior of the driver among a spectrum of behavior classifications, based at least in part on operational data about the vehicle collected in real time by sensors of the vehicle, and the current level of stress or drowsiness of the driver determined by the first multi-layer neural network in real time;
a safety action engine operated by a processor in the vehicle and coupled to the second multilayer neural network to determine a safety related action, based at least in part on the determined driver behavior classification and data related to current traffic or road condition of a route the vehicle is currently traveling on; and
an infotainment system or a navigation system disposed in the vehicle to perform the safety related action to assist the driver in driving the vehicle in a safer manner.
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Abstract
Methods and apparatuses for safety enhanced computer-assisted driving. In embodiments, an apparatus for computer-assisted driving may include a neural network to determine a classification for behavior of a driver of a vehicle having the apparatus, based at least in part on data about the vehicle collected in real time, and a current level of stress or drowsiness of the driver determined in real time; and a safety action engine coupled to the neural network to determine a safety related action, based at least in part on the determined driver behavior classification and data related to current traffic or road condition of a route the vehicles is currently traveling on. The safety related action may be performed by an infotainment system or a navigation system of the vehicle to assist the driver in driving the vehicle in a safer manner.
16 Citations
20 Claims
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1. An apparatus for computer-assisted driving, comprising:
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a communication interface to receive, from a wearable device worn by a driver of a vehicle, a current level of stress or drowsiness of the driver, wherein the wearable device includes a first multilayer neural network to locally determine the current level of stress or drowsiness of the driver, based at least in part on physiological data of the driver collected in real time by the wearable device worn by the driver; a second multilayer neural network implemented with a hardware accelerator in the vehicle and coupled with the communication interface to locally determine a classification for behavior of the driver among a spectrum of behavior classifications, based at least in part on operational data about the vehicle collected in real time by sensors of the vehicle, and the current level of stress or drowsiness of the driver determined by the first multi-layer neural network in real time; a safety action engine operated by a processor in the vehicle and coupled to the second multilayer neural network to determine a safety related action, based at least in part on the determined driver behavior classification and data related to current traffic or road condition of a route the vehicle is currently traveling on; and an infotainment system or a navigation system disposed in the vehicle to perform the safety related action to assist the driver in driving the vehicle in a safer manner. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for computer assisted driving, comprising:
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receiving, from a first multilayer neural network disposed in a wearable device worn by a driver of a vehicle, by a second multilayer neural network disposed in the vehicle, a current level of stress or drowsiness of a driver of the vehicle, based at least in part on physiological data of the driver collected in real time by sensors of the wearable device; determining locally, with the second multilayer neural network disposed in the vehicle, a classification for behavior of the driver of the vehicle among a spectrum of behavior classifications, based at least in part on operational data about the vehicle collected in real time, and the current level of stress or drowsiness of the driver determined by the first multilayer neural network; and determining locally, with a safety action engine, a safety related action, based at least in part on the determined driver behavior classification and data related to current traffic or road condition of a route the vehicle is currently traveling on; wherein the determined safety related action assists the driver in driving the vehicle in a safer manner. - View Dependent Claims (12, 13, 14)
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15. At least one non-transitory computer readable media (CRM) comprising a plurality of instructions arranged to cause an infotainment system or a navigation system of an in-vehicle system disposed in a vehicle, in response to execution of the instructions by a processor of the in-vehicle system, to:
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receive from a first multilayer neural network disposed in a wearable device worn by a driver of the vehicle, for a second multilayer neural network of the vehicle, a current level of stress or drowsiness of the driver of the vehicle, determined in real time based at least in part on physiological data of the driver collected in real time by sensors of the wearable device; receive from the second multilayer neural network of the vehicle a classification for behavior of the driver of the vehicle among a spectrum of behavior classifications, locally determined in real time based at least in part on operational data about the vehicle collected in real time, and the current level of stress or drowsiness of the driver determined by the first multilayer neural network; and determine locally, with a safety action engine, a safety related action to be performed by the infotainment system or the navigation system of the vehicle to assist the driver in driving the vehicle in a safer manner, based at least in part on the classification for behavior of the driver, and data related to current traffic or road condition of a route the vehicle is currently traveling on. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification