An example operation includes one or more of determining a level of risk of a collision of a transport, wherein the level of risk is related to an occupant of the transport and an environment of the transport, accumulating an amount of data based on the level of risk, preparing the accumulated data for sending to one or more recipients when the level of risk exceeds a risk threshold, and sending the prepared data to the one or more recipients when the collision occurs.

An example operation includes one or more of determining a level of risk of a collision of a transport, wherein the level of risk is related to an occupant of the transport and an environment of the transport, accumulating an amount of data based on the level of risk, preparing the accumulated data for sending to one or more recipients when the level of risk exceeds a risk threshold, and sending the prepared data to the one or more recipients when the collision occurs.

An example operation includes one or more of determining a characteristic of an occupant in a transport and a current driving environment of the transport, wherein the characteristic includes a position of the occupant, determining that the current driving environment will lead to a collision of the transport, and based on a predicted result of the collision, sending a predicted state of the occupant based on the position, to an emergency service node.

The disclosed embodiments include a onboard driver distraction determination system. The determination system includes a onboard sensing and computing system(s), which includes inertial sensor(s), internal sensor(s), and external sensor(s). The onboard system samples data from the sensor(s) during a driving session to determine steering activity metrics and driver behavior. A steering activity metric is a representation of the steering inputs by the driver during the driving session. Driver behavior is a representation of how distracted the driver is during the driving session. By performing the above mentioned steps, the system can provide an analysis of driver distraction and optionally, take control of the vehicle to avoid aberrant behavior.

Systems and methods are disclosed for monitoring or affecting movement of a vehicle using a traffic device. An event data source may have a processor and/or a transceiver. The event data source may transmit, via the transceiver and to a vehicle and infrastructure computing device, information indicative of an event affecting a portion of road. The vehicle and infrastructure computing device may comprise a vehicle and infrastructure control computer. The vehicle and infrastructure computing device may receive, from the event data source, the information indicative of the event affecting the portion of road. The computing device may determine one or more traffic devices associated with the portion of road and configured to control traffic for the portion of road. Based on the information indicative of the event affecting the portion of road, the computing device may send, to the one or more traffic devices associated with the portion of road, instructions to change one or more characteristics of the one or more traffic devices.

A sleepiness estimating device including an auxiliary information acquirer that acquires auxiliary information including at least one of five-sense information perceived by a person or emotion information indicating an emotion of the person; and a sleepiness estimator that estimates a sleepiness of the person based on the auxiliary information.

A sleepiness estimating device including an auxiliary information acquirer that acquires auxiliary information including at least one of five-sense information perceived by a person or emotion information indicating an emotion of the person; and a sleepiness estimator that estimates a sleepiness of the person based on the auxiliary information.

Disclosed are a fatigue state detection method and apparatus, a medium and a device. The method includes: obtaining image blocks containing an organ area of a target object from a plurality of video frames collected by a camera apparatus disposed in a mobile device, to obtain an image-block sequence that is based on the organ area; determining a fatigue state type of the target object based on the image-block sequence of the organ area; sending the image-block sequence to a cloud server if the fatigue state type meets a first preset type, and rendering the cloud server to detect a fatigue level of the target object based on the image-block sequence; and receiving fatigue level information about the target object that is returned by the cloud server. The present disclosure may improve accuracy of fatigue state detection, thereby helping to improve driving safety of the mobile device.

Disclosed are a fatigue state detection method and apparatus, a medium and a device. The method includes: obtaining image blocks containing an organ area of a target object from a plurality of video frames collected by a camera apparatus disposed in a mobile device, to obtain an image-block sequence that is based on the organ area; determining a fatigue state type of the target object based on the image-block sequence of the organ area; sending the image-block sequence to a cloud server if the fatigue state type meets a first preset type, and rendering the cloud server to detect a fatigue level of the target object based on the image-block sequence; and receiving fatigue level information about the target object that is returned by the cloud server. The present disclosure may improve accuracy of fatigue state detection, thereby helping to improve driving safety of the mobile device.

Systems and methods to authenticate a vehicle operator for an autonomous vehicle on a vehicle service platform are provided. In one example embodiment, a computer-implemented method includes obtaining authentication request data indicative of an authentication request, the authentication request data including at least an operator identifier associated with the vehicle operator and a vehicle identifier associated with the autonomous vehicle. The method includes providing a service code associated with the authentication request to the autonomous vehicle. The method includes obtaining from a user device in response to providing the service code to the autonomous vehicle, operator data associated with the authentication request, the operator data including the service code. The method includes determining an authentication result associated with the authentication request based at least in part on the service code and the operator data. The method includes providing the authentication result to the user device.