Systems and methods are disclosed. A digitized human vocal expression of a user and digital images are received over a network from a remote device. The digitized human vocal expression is processed to determine characteristics of the human vocal expression, including: pitch, volume, rapidity, a magnitude spectrum identify, and/or pauses in speech. Digital images are received and processed to detect characteristics of the user face, including detecting if any of the following is present: a sagging lip, a crooked smile, uneven eyebrows, and/or facial droop. Using the human vocal expression characteristics and face characteristics, a determination is made as to what action is to be taken. A cepstrum pitch may be determined using an inverse Fourier transform of a logarithm of a spectrum of a human vocal expression signal. The volume may be determined using peak heights in a power spectrum of the human vocal expression.

Techniques are described for cognitive analysis for directed control transfer for autonomous vehicles. In-vehicle sensors are used to collect cognitive state data for an individual within a vehicle which has an autonomous mode of operation. The cognitive state data includes infrared, facial, audio, or biosensor data. One or more processors analyze the cognitive state data collected from the individual to produce cognitive state information. The cognitive state information includes a subset or summary of cognitive state data, or an analysis of the cognitive state data. The individual is scored based on the cognitive state information to produce a cognitive scoring metric. A state of operation is determined for the vehicle. A condition of the individual is evaluated based on the cognitive scoring metric. Control is transferred between the vehicle and the individual based on the state of operation of the vehicle and the condition of the individual.

An apparatus and method for monitoring a vehicle driver having at least one sensor for measuring pressure and/or humidity. The sensor includes at least one capacitor having at least two electrodes, which may be arranged horizontally on a flexible support material. At least one dielectric layer may be arranged between the electrodes. At least one electrode, and/or the dielectric layer, and at least one, at least partially liquid-permeable and/or liquid-absorbing moisture layer may be arranged on a side facing away from a support material. At least one electrode and/or the dielectric layer may be arranged transversely between the support material and the moisture layer. A capacitance may be changed by liquid on the dielectric layer, and a processing unit measures and/or stores values from the sensor, creating a capacitive humidity sensor. The processing unit may send the to a central CPU, wherein this data may be processed by the processing unit.

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.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status and/or configuration of autonomous operation features of an autonomous or semi-autonomous vehicle may be determined, such as via an on-board computer system or mobile device, and/or then directly or indirectly wirelessly communicated via data transmission from the vehicle computer system or mobile device to a remote server. An adjustment to one or more risk levels associated with operation of the autonomous or semi-autonomous vehicle may also be determined, and an auto insurance policy, premium, or discount may be adjusted based upon the adjustment to the risk levels and presented to the customer for their review and approval. As a result, insurance cost savings may be passed onto risk averse customers that opt into to a rewards program.

An information processing apparatus communicable with a vehicle includes a controller. The controller is configured to store behavior information of a user in the vehicle in association with a date and time, acquire an image via an imaging unit of the vehicle when a difference between behavior information at a specific time and behavior information at a time later than the specific time is detected, an store the image in association with the date and time and the behavior information.

A vehicle may include: a feedback device; a bio-signal sensor configured to measure a bio-signal of a user; and a controller operatively coupled to the feedback device and the bio-signal sensor, the controller including a memory configured to store at least one program instruction and processor configured to execute the at least one program instruction. The controller may be configured to: determine information characterizing a current emotional state of the user based on the bio-signal; calculate, based on a difference value between the current emotional state and a target emotional state, an operation ratio between a first mode for controlling operation of the feedback device to decrease a degree of excitability of the user and a second mode for controlling the operation of the feedback device to increase a degree of positivity of the user; and control the operation of the feedback device for a predetermined time based on the operation ratio.

According to one aspect, systems, methods, and/or techniques associated with operator take-over prediction may include receiving a two-channel series of images of an operating environment through which a vehicle is travelling. A first series of images may be represented by labels corresponding to classified objects. A second series of images may be represented as a gaze heatmap or an eye tracking heatmap. Additionally, feeding encoded series of images through a three-dimensional (3D) convolutional neural network (CNN) to produce a first output, receiving sets of information corresponding to a first series of images and a second series of images in time, feeding sets of information through processing layers to produce additional outputs, concatenating the first output and the additional outputs to produce a concatenation output, and feeding the concatenation output through additional processing layers to generate an operator take-over prediction may be performed.

A technique for enabling efficient retrieval of a digital representation of personality data of a user (402) by a client device (406) from a server (404) is disclosed, wherein the digital representation of the personality data is processed at the client device (406) to provide a user-adapted service to the user (402). A method implementation of the technique is performed by the server (404) and comprises storing a neural network being trained to compute personality data of a user based on input obtained from the user (402), receiving, from the client device (406), a request for a digital representation of personality data for a user (402), and sending, to the client device (406), the requested digital representation of the personality data of the user (402), wherein the personality data of the user is computed using the neural network based on input obtained from the user (402).

The present teaching relates to method, system, medium, and implementation of automatic motion planning for an autonomous driving vehicle. Information is obtained with respect to a current location of the autonomous driving vehicle operating in a current vehicle motion, wherein the information is to be used to estimate the operational capability of the autonomous driving vehicle with respect to the current location. Sensor data are obtained, via one or more sensors in one or more media types. A reaction of a passenger present in the vehicle with respect to a current vehicle motion is estimated based on the sensor data. Motion planning is performed based on the information with respect to the current location and the reaction of the passenger to the current vehicle motion.