A method for augmenting transport services using event detection is provided. The method includes collection of first sensor data generated by various sensors associated with a plurality of vehicles. The first sensor data includes sensor outputs that indicate a plurality of rash driving events. The sensor outputs are augmented based on angular rotation to obtain augmented sensor outputs. A prediction model is trained based on the augmented sensor outputs. Target sensor data associated with a target vehicle is provided as input to the trained prediction model, and based on an output of the trained prediction model an occurrence of a rash driving event is detected in real-time or near real-time. Based on a count of rash driving events associated with the target driver within a cumulative driving distance, a driver score of the target driver is determined.

An embodiment of the invention provides a method to control a mechanical system based on the cognitive state of a user, where a first action is performed at an input device that is associated with the user. The cognitive state of the user is detected at the input device; and, a change to the first action is determined based on the cognitive state of the user. A controlled action is performed based on the recommended change. A system can include an input device associated with user, where a first action is performed at the input device. A processor connected to the input device detects the cognitive state of the user at the input device and determines a change to the first action based on the cognitive state of the user. A controller connected to the processor performs a controlled action based on the recommended change.

One or more braking event detection computing devices and methods are disclosed herein based on fused sensor data collected during a window of time from various sensors of a mobile device found within an interior of a vehicle. The various sensors of the mobile device may include a GPS receiver, an accelerometer, a gyroscope, a microphone, a camera, and a magnetometer. Data from vehicle sensors and other external systems may also be used. The braking event detection computing devices may adjust the polling frequency of the GPS receiver of the mobile device to capture non-consecutive data points based on the speed of the vehicle, the battery status of the mobile device, traffic-related information, and weather-related information. The braking event detection computing devices may use classification machine learning algorithms on the fused sensor data to determine whether or not to classify a window of time as a braking event.

This disclosure relates to a system and method for transitioning vehicle control between autonomous operation and manual operation. The system includes sensors configured to generate output signals conveying information related to the vehicle and its operation. During autonomous vehicle operation, the system gauges the level of responsiveness of a vehicle operator through challenges and corresponding responses. The system determines when to present a challenge to the vehicle operator based on internal and external factors. If necessary, the system will transition from an autonomous operation mode to a manual operation mode.

A vehicular awakening detection device 10 includes pressure sensors 48 provided in a + side paddle shift 46R and/or a − side paddle shift 46L which is able to be operated by a driver in a vehicle. The pressure sensor 48 is used for determining the degrees of awakening of a driver by making the driver to operate the + side paddle shift 46R and/or the − side paddle shift 46L.

In some implementations, a device may receive historical telematics data associated with a vehicle. The device may determine a set of base line driving parameters based on the historical telematics data. The device may receive current telematics data associated with the vehicle. The device may determine a set of current driving parameters based on the current telematics data. The device may determine, based on processing the set of base line driving parameters and the set of current driving parameters with a machine learning model, a type of driving behavior of a driver of the vehicle. The device may determine, based on processing the set of base line driving parameters and the set of current driving parameters with another machine learning model, a severity score associated with the type of driving behavior. The device may perform an action based on the type of driving behavior and the severity score.

System, methods, and other embodiments described herein relate to improving event management in a vehicle by aggregating information sources. In one embodiment, a method includes selecting unfiltered events, from a stream of events that are classified and filtered, and a display medium according to a decision policy associated with an operator. The method also includes communicating the unfiltered events selected for the display medium. The method also includes adapting the decision policy according to collected tracking information of operator attention associated with the unfiltered events and reward values associated with the tracking information.

An information presenting apparatus is used in an autonomous vehicle capable of switching between autonomous driving control and manual driving control. The information presenting apparatus determines a response action for checking that the driver is ready to take over when the autonomous driving control is switched to the manual driving control, performs control for requesting the driver to perform the response action determined, and detects the response action performed by the driver.

Systems and methods are described herein for managing communications for a connected vehicle, such as between the connected vehicle and other connected vehicle and/or between the connected vehicle and infrastructure entities, such as providers of services to the connected vehicle. For example, a communication network, such as a network provided by a network carrier, may include various cloud engines or other network-based servers that manage, coordinate, and/or provision communications between the connected vehicle and other parties, such as vehicles, road devices, buildings, and other infrastructure entities.

Provided is a wearable device including a main body that is configured to be worn on a specific portion of a user's body, a sensing unit, provided in the main body, that senses a biological signal of a user, a storage unit that collects log information relating to the biological signal, and in which an index pattern relating to a state of the user included in the collected log information is stored, and a controller that sets a reference driving index, using the stored index pattern, in which when it is sensed that the user gets in a vehicle, the controller determines a current driving index corresponding to the biological signal that is sensed before and after the user gets in the vehicle, based on the reference driving index being set, and outputs feedback that notifies the state of the user that corresponds to a result of the determination.